Template-Type: ReDIF-Article 1.0 Author-Name: Giovanni Pirovano Author-X-Name-First: Giovanni Author-X-Name-Last: Pirovano Author-Name: Federica Ciccullo Author-X-Name-First: Federica Author-X-Name-Last: Ciccullo Author-Name: Margherita Pero Author-X-Name-First: Margherita Author-X-Name-Last: Pero Author-Name: Tommaso Rossi Author-X-Name-First: Tommaso Author-X-Name-Last: Rossi Title: Scheduling batches with time constraints in wafer fabrication Abstract: This work proposes and tests an algorithm for batching and dispatching lots along cleaning and diffusion operations of a wafer fab. These are characterised by: 1) time constraints (i.e., the time between the end of an operation 'n' and the start of the operation 'n + q' must be lower than a time limit, in order to guarantee the lots' quality); 2) absence of batching affinity between operations. Literature so far has been falling short in proposing scheduling algorithms suitable for this context. Therefore, we propose two heuristic algorithms to minimise the average flow time and the number of re-cleaned lots, maximise machine saturation and avoid scrapped lots. Discrete-event simulation was used to test the performance of the two algorithms using real data of STMicroelectronics. The formerly proposed model outperforms the latter. Therefore, STMicroelectronics implemented the former in its fab in Catania gaining an increase in the average Overall equipment effectiveness of 7%. Journal: Int. J. of Operational Research Pages: 1-31 Issue: 1 Volume: 37 Year: 2020 Keywords: semiconductor manufacturing; dispatching rules; batch; scheduling; wafer fab; time constraints; diffusion; STMicroelectronics. File-URL: http://www.inderscience.com/link.php?id=104222 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:1:p:1-31 Template-Type: ReDIF-Article 1.0 Author-Name: Susanta Banik Author-X-Name-First: Susanta Author-X-Name-Last: Banik Author-Name: Debasish Bhattacharya Author-X-Name-First: Debasish Author-X-Name-Last: Bhattacharya Title: A note on min-max goal programming approach for solving multi-objective de novo programming problems Abstract: Min-max goal programming approach for solving multi-objective de novo programming problems was studied by Nurullah Umarusman in 2013. The present study is a further attempt to examine the approach and present an improved version of the approach. In Umarusman's method, each of the goal constraints is having both positive and negative deviation variables, whereas in the proposed approach only one deviation variable has been used. The method of solution has been illustrated with the numerical examples. The solution obtained by proposed method yields objective values which are better than those obtained by Umarusman for the same set of weights. Journal: Int. J. of Operational Research Pages: 32-47 Issue: 1 Volume: 37 Year: 2020 Keywords: optimal system design; de novo programming; min-max goal programming; multi-objective optimisation. File-URL: http://www.inderscience.com/link.php?id=104223 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:1:p:32-47 Template-Type: ReDIF-Article 1.0 Author-Name: Faizul Huq Author-X-Name-First: Faizul Author-X-Name-Last: Huq Author-Name: Trevor S. Hale Author-X-Name-First: Trevor S. Author-X-Name-Last: Hale Author-Name: Nikhil A. Pujari Author-X-Name-First: Nikhil A. Author-X-Name-Last: Pujari Title: A continuous approximation procedure for determining inventory distribution schemas within supply chains: gradual and intermittent shipping patterns Abstract: The popularity of supply chain integration models is increasing. The research in this paper builds upon prior research and presents an integrated inventory supply chain optimisation model that incorporates the issues of location, production, inventory, and transportation simultaneously. The objective of the current research is to determine the optimal number as well as the optimal size of shipments under a variety of production and shipping rate scenarios. Previous research in this area assumed instantaneous shipping. Herein, this assumption is generalised to include a non-instantaneous, gradual shipping pattern as well as staggered, more intermittent shipping pattern. These two more generalised shipping scenarios (each with several sub-scenarios) are investigated and closed form expressions for the optimal number and the optimal size of shipments for each scenario are obtained. A detailed numerical example is presented to demonstrate the efficacy of the approach. Journal: Int. J. of Operational Research Pages: 48-84 Issue: 1 Volume: 37 Year: 2020 Keywords: distribution system; inventory management; supply chain; continuous approximation; shipping pattern. File-URL: http://www.inderscience.com/link.php?id=104224 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:1:p:48-84 Template-Type: ReDIF-Article 1.0 Author-Name: Mohammad Ebrahim Bolouri Author-X-Name-First: Mohammad Ebrahim Author-X-Name-Last: Bolouri Author-Name: Shokrollah Ziari Author-X-Name-First: Shokrollah Author-X-Name-Last: Ziari Author-Name: Ali Ebrahimnejad Author-X-Name-First: Ali Author-X-Name-Last: Ebrahimnejad Title: New approach for ranking efficient DMUs based on Euclidean norm in data envelopment analysis Abstract: Data envelopment analysis (DEA) is a widely used technique for measuring the relative efficiencies of decision-making unit (DMUs) with multiple inputs and multiple outputs. In many applications, ranking of DMUs is an important and essential procedure to decision makers in DEA, especially when there are extremely efficient DMUs. Basic DEA models usually give the same efficiency score for some DMUs. Hence, it is necessary to rank of all extreme DMUs. The main purpose of this study is to propose an appropriate method in order to overcome the drawbacks in several methods for ranking DMUs based on the DEA concept. In the present paper, we propose a model for ranking extreme efficient DMUs in DEA by super efficiency technique and Euclidean norm (<i>ℓ</i><SUB align="right"><SMALL>2</SMALL></SUB>-norm). The presented method in this paper is able to overcome the existing obstacles in some methods. As regards, the proposed model is into nonlinear programming form, a linear model is suggested to approximate the nonlinear model. Journal: Int. J. of Operational Research Pages: 85-104 Issue: 1 Volume: 37 Year: 2020 Keywords: data envelopment analysis; DEA; ranking; efficiency; extreme efficient; Euclidean norm. File-URL: http://www.inderscience.com/link.php?id=104225 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:1:p:85-104 Template-Type: ReDIF-Article 1.0 Author-Name: Robert Ebihart Msigwa Author-X-Name-First: Robert Ebihart Author-X-Name-Last: Msigwa Author-Name: Yue Lu Author-X-Name-First: Yue Author-X-Name-Last: Lu Author-Name: Li-Wei Zhang Author-X-Name-First: Li-Wei Author-X-Name-Last: Zhang Title: A perturbation-based approach for continuous network design problem with link capacity expansion Abstract: This paper formulates a continuous network design problem (CNDP) as a nonlinear mathematical program with complementarity constraints (NLMPCC) and then a perturbation-based approach is proposed to overcome the NLMPCC problem and the lack of constraint qualifications. This formulation permits a more general route cost structure and every stationary point of it corresponds to a global optimal solution of the perturbed problem. The contribution of this paper from the mathematical perspective is that, instead of using the conventional nonlinear programming methodology, variational analysis is taken as a tool to analyse the convergence of the perturbation-based method. From the practical point of view, a convergent algorithm is proposed for the CNDP and employs the sequential quadratic program (SQP) solver to obtain the solution of the perturbed problem. Numerical experiments are carried out in both 16 and 76-link road networks to illustrate the capability of the perturbation-based approach to the CNDP with elastic demand. Results showed that the proposed model will solve a wider class of transportation equilibrium problems than the existing ones. Journal: Int. J. of Operational Research Pages: 105-134 Issue: 1 Volume: 37 Year: 2020 Keywords: continuous network design problem; CNDP; bilevel programming; nonlinear mathematical program with complementarity constraints; MPCC; variational analysis; perturbation-based approach. File-URL: http://www.inderscience.com/link.php?id=104226 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:1:p:105-134 Template-Type: ReDIF-Article 1.0 Author-Name: Kailash Lachhwani Author-X-Name-First: Kailash Author-X-Name-Last: Lachhwani Title: On multi-level quadratic fractional programming problem with modified fuzzy goal programming approach Abstract: The present paper addresses an extended algorithm for the solution of multi-level quadratic fractional programming problem(ML-QFPP) based on fuzzy goal programming (FGP) approach. In this algorithm, suitable linear and nonlinear membership functions for the fuzzily described numerator and denominator of the quadratic objective functions of all levels as well as the control vectors of higher levels are respectively defined using individual optimal solutions. Then usual fuzzy goal programming approach is applied for the achievement of highest degree of each of the membership goal by minimising the negative deviational variables. The proposed algorithm is an extension of modified FGP approach for ML-QFPPs and a simple algorithm to obtain compromise optimal solution of ML-QFPPs with all major types of nonlinear membership functions. Comparative analysis over the variation in the types of membership functions is also carried out with numerical example to show suitability of different membership functions in the proposed algorithm. Journal: Int. J. of Operational Research Pages: 135-156 Issue: 1 Volume: 37 Year: 2020 Keywords: multi-level quadratic fractional programming; ML-QFPP; fuzzy goal programming; FGP; membership function; negative deviational variable; compromise optimal solution. File-URL: http://www.inderscience.com/link.php?id=104227 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:1:p:135-156 Template-Type: ReDIF-Article 1.0 Author-Name: Aicha Anzi Author-X-Name-First: Aicha Author-X-Name-Last: Anzi Author-Name: Mohammed Said Radjef Author-X-Name-First: Mohammed Said Author-X-Name-Last: Radjef Title: Solving a class of multiobjective bilevel problems by DC programming Abstract: In this paper, we consider a class of multiobjective bilevel programming problems in which the first level objective function is assumed to be a vector valued DC function and the second level problem is a linear multiobjective program. The problem is transformed into a standard single optimisation problem by using a preference function. We give a characterisation to the induced region and reformulate the problem as a problem of optimising a function over the efficient set. Next, a well-known representation of the efficient set is used which will allow to transform the problem, using an exact penalisation, into a DC program. Finally, we apply the DC algorithm to solve the resulting DC program. Journal: Int. J. of Operational Research Pages: 157-173 Issue: 2 Volume: 37 Year: 2020 Keywords: bilevel programming; multiobjective optimisation; exact penalty; DC algorithm; DCA; DC programming; preference function. File-URL: http://www.inderscience.com/link.php?id=105364 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:2:p:157-173 Template-Type: ReDIF-Article 1.0 Author-Name: R. Anitha Author-X-Name-First: R. Author-X-Name-Last: Anitha Author-Name: S. Jeyadevi Author-X-Name-First: S. Author-X-Name-Last: Jeyadevi Title: Gravitational search algorithm-based UPQC for power quality improvement of WECS Abstract: The design of merged presentation of UPQC and WECS is conscientious for extenuating the PQ problems of distribution scheme in the work. The projected scheme is unruffled of WECS, sequences and shunt APF joined to DC link that is capable to compensate the voltage sag, swell, harmonics and voltage interruption. Currently, the recompense approach of UPQC is examined with GSA. Here, GSA is engaged to enhance the control pulses of UPQC. To acquire optimal performance of the distribution system, these faults are diminished and producing the optimal control signals. The expected scheme is capable to bring in the active power to grid also its competence in augmentation of power quality in distribution scheme. The presentation of the expected GSA-based UPQC scheme is corroborated over simulations by MATLAB/Simulink and compared with the traditional approaches such as ANFIS-based UPQC and GA-based UPQC. Journal: Int. J. of Operational Research Pages: 259-292 Issue: 2 Volume: 37 Year: 2020 Keywords: unified power quality compensator; UPQC; gravitational search algorithm; GSA; adaptive neuro-fuzzy inference system; ANFIS; genetic algorithm; series and shunt APF; voltage; current; real and reactive power. File-URL: http://www.inderscience.com/link.php?id=105365 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:2:p:259-292 Template-Type: ReDIF-Article 1.0 Author-Name: Bharathi Lakshmanan Author-X-Name-First: Bharathi Author-X-Name-Last: Lakshmanan Author-Name: Sasikala Ramasamy Author-X-Name-First: Sasikala Author-X-Name-Last: Ramasamy Author-Name: Srinivasan Alavandar Author-X-Name-First: Srinivasan Author-X-Name-Last: Alavandar Title: Hybrid approach for a reliable bufferless OBS network with reduced end-to-end delay and burst loss Abstract: Optical burst switching (OBS) is a very efficient all optical transmission network. But the performance of the network may reduce because of the burst losses. Hence, to eliminate the collision and dropping of packets at the core nodes we have proposed a hybrid approach for a reliable bufferless OBS network known as an enhanced multipath adaptive burst assembly algorithm (EMP-ABAA). In this technique based on the priority and type of users (i.e., regular users with lesser priority and premium users with high priority), data packets are routed efficiently. At the core nodes the relative drop in data packet, delivery ratio, delay and energy consumption is evaluated in comparison with FAHBA approach. From the simulation results, using NS2 simulation, it is observed that the proposed approach outperforms FAHBA approach; hence enhancing the efficiency and reliability of the OBS network with lesser overhead utilisation in the network. Journal: Int. J. of Operational Research Pages: 220-244 Issue: 2 Volume: 37 Year: 2020 Keywords: optical burst switching; OBS; core nodes; latency; fuzzy logic; routing. File-URL: http://www.inderscience.com/link.php?id=105366 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:2:p:220-244 Template-Type: ReDIF-Article 1.0 Author-Name: Arindam Garai Author-X-Name-First: Arindam Author-X-Name-Last: Garai Author-Name: Palash Mandal Author-X-Name-First: Palash Author-X-Name-Last: Mandal Author-Name: Tapan Kumar Roy Author-X-Name-First: Tapan Kumar Author-X-Name-Last: Roy Title: Solutions of multiple objective linear programming problems by applying T-sets in imprecise environment Abstract: In this paper, technique to find Pareto optimal solutions to multiple objective linear programming problems under imprecise environment is discussed. In imprecise environment, we observe that more preferable optimal values may be obtained by allowing membership functions to take arbitrary values, i.e., by removing constraints that impose membership values to fall in range between zero and one, than existing fuzzy optimisation techniques. Further, membership functions are not utilised as per definitions in existing fuzzy optimisation techniques. Also, such constraints may make the model infeasible. Consequently, one set viz. T-set is defined to supersede fuzzy set to represent impreciseness. Next, one general algorithm comprising T-sets, is given to find Pareto optimal solutions to multiple objective linear programming problems in imprecise environment. Numerical examples further illustrate proposed algorithm. Finally conclusions are drawn. Journal: Int. J. of Operational Research Pages: 198-219 Issue: 2 Volume: 37 Year: 2020 Keywords: multiple objective decision making; fuzzy set; fuzzy mathematical programming; linear programming problem; T-Pareto optimal solution; T-characteristic function; T-set; fuzzy decision making; optimisation. File-URL: http://www.inderscience.com/link.php?id=105367 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:2:p:198-219 Template-Type: ReDIF-Article 1.0 Author-Name: Rajendran Manivasagam Author-X-Name-First: Rajendran Author-X-Name-Last: Manivasagam Author-Name: Rajendran Prabakaran Author-X-Name-First: Rajendran Author-X-Name-Last: Prabakaran Title: Power quality improvement by UPQC using ANFIS-based hysteresis controller Abstract: In this paper, an adaptive neuro-fuzzy interference system (ANFIS) that is based on hysteresis controller is being proposed for achieving the power quality improvement. The innovatory ideas behind this methodology are the smoothness obtained with the fuzzy interpolation and the adaptability for complex problems using the neural network back propagation. In addition, the neural network renders increased control over the output voltage of the series active power filter (APF) and the output current of the shunt APF too. Here, the ANFIS is trained using the target control signals of both the series APF as well as the shunt APF and with the corresponding input source side and load side parameters of the system. During the testing time, the UPQC is controlled using the control signals that are attained from the ANFIS. With the utilisation of the proposed method, the voltage and the current perturbations are reduced and the system power quality is enhanced. The MATLAB/Simulink platforms are used to execute the proposed control technique and the presentation is examined using different types of source voltage fault conditions. The effectiveness of the proposed ANFIS-based controller is analysed through the comparison analysis with the conventional control techniques. Journal: Int. J. of Operational Research Pages: 174-197 Issue: 2 Volume: 37 Year: 2020 Keywords: unified power quality conditioner; UPQC; adaptive neuro-fuzzy interference system; ANFIS; power quality; series APF; shunt APF; voltage; current. File-URL: http://www.inderscience.com/link.php?id=105368 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:2:p:174-197 Template-Type: ReDIF-Article 1.0 Author-Name: Mohamed Abd Allah El-Hadidy Author-X-Name-First: Mohamed Abd Allah Author-X-Name-Last: El-Hadidy Title: On the existence of a finite linear search plan with random distances and velocities for a one-dimensional Brownian target Abstract: In this paper, we consider a linear search model that takes into consideration the velocities and the distances which the searcher do them are independent random variables with known probability density functions (PDFs). The searcher moves continuously along the line in both directions of the starting point (origin of line). We use the Fourier-Laplace representation to give an analytical expression for the density of the random distance in the model. Also, we get the conditions that make the expected value of the first meeting time between the searcher and the target is finite. Journal: Int. J. of Operational Research Pages: 245-258 Issue: 2 Volume: 37 Year: 2020 Keywords: linear search problem; finite search plan; one-dimensional Brownian motion; Fourier-Laplace transform. File-URL: http://www.inderscience.com/link.php?id=105369 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:2:p:245-258 Template-Type: ReDIF-Article 1.0 Author-Name: K. Vidhya Author-X-Name-First: K. Author-X-Name-Last: Vidhya Title: Performance of MIMO-OFDM systems Abstract: Orthogonal frequency division multiplexing (OFDM) is one of the new modulation techniques which is used to combat the frequency-selectivity of the transmission channel models achieving high data rate without inter-symbol interference. OFDM may be combined with antenna arrays at the transmitter and receiver to increase the system capacity on time-variant and frequency-selective channel models resulting in a multiple-input multiple-output (MIMO) configuration. In this paper, SISO, SIMO, MISO and MIMO-OFDM configurations of OFDM systems are proposed. LS channel estimator is used to calculate the channel coefficients. The four different OFDM systems are analysed and simulated. The simulation consists of four parameters namely bit error rate, mean square error, symbol error rate and capacity of the channel for MIMO-OFDM systems. The error rate values are minimised in 2×2 MIMO-OFDM systems compared to other 1×1, 1×2, 2×1 OFDM systems. Similarly channel capacity is maximised in 2×2 MIMO-OFDM systems, compared to the other OFDM systems. These performances are implemented using MATLAB software. Journal: Int. J. of Operational Research Pages: 293-306 Issue: 2 Volume: 37 Year: 2020 Keywords: multiple input multiple output; MIMO; OFDM systems; single input single output; SISO; single input multiple output; SIMO. File-URL: http://www.inderscience.com/link.php?id=105370 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:2:p:293-306 Template-Type: ReDIF-Article 1.0 Author-Name: Sanat Kumar Mahato Author-X-Name-First: Sanat Kumar Author-X-Name-Last: Mahato Author-Name: Nabaranjan Bhattacharyee Author-X-Name-First: Nabaranjan Author-X-Name-Last: Bhattacharyee Author-Name: Rajesh Pramanik Author-X-Name-First: Rajesh Author-X-Name-Last: Pramanik Title: Fuzzy reliability redundancy optimisation with signed distance method for defuzzification using genetic algorithm Abstract: Consideration of impreciseness is more realistic for modelling of physical phenomena. This impreciseness can be considered in several ways like, interval/stochastic/fuzzy or mixture of these. In this work, we have taken for optimising of the system reliability of a redundancy allocation problem formulated from a complex network system with imprecise parameters in the form of trapezoidal fuzzy numbers (TrFN). The signed distance method has been used to defuzzify the fuzzy values. Then big-M penalty technique is used to transform the problem to unconstrained optimisation problem. To solve these problems, we have implemented the real coded elitist genetic algorithm (RCEGA) for integer variables with tournament selection, intermediate crossover and one neighbourhood mutation. For illustration, the five link bridge network system has been solved and the results have been presented. Journal: Int. J. of Operational Research Pages: 307-323 Issue: 3 Volume: 37 Year: 2020 Keywords: reliability-redundancy allocation; imprecise environment; genetic algorithm; fuzzy number; defuzzification; signed distance method; SDM; penalty function. File-URL: http://www.inderscience.com/link.php?id=105441 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:3:p:307-323 Template-Type: ReDIF-Article 1.0 Author-Name: Vivek D. Kalyankar Author-X-Name-First: Vivek D. Author-X-Name-Last: Kalyankar Author-Name: Ajinkya V. Musale Author-X-Name-First: Ajinkya V. Author-X-Name-Last: Musale Title: Design optimisation of vehicle suspension systems using artificial intelligent techniques Abstract: Suspension system plays important role in automobiles and to some extent it is treated as backbone of vehicles. Design of suspension systems present challenges because of different conflicting criteria's and hence, optimum design of its parameters is essential to get better ride comfort. Important design parameters involved in suspension systems are un-sprung mass, sprung mass, tire stiffness, spring stiffness, suspension damping coefficient, etc.; and obtaining optimum design combination of all these parameters is only possible with the use of appropriate optimisation techniques. This article presents the summary of various optimisation techniques used by previous researchers for design optimisation of suspension systems. It is observed that, despite having various evolutionary optimisation techniques, most of the earlier work was surrounded with traditional methods and genetic algorithm. Hence, a better performing algorithm compared to those, is demonstrated here to prove, uses of appropriate algorithm will help to improve the performance of suspension systems. A swarm based artificial bee colony algorithm is considered here to achieve optimum design and it is demonstrated with two examples having different road conditions. Results obtained shows considerable improvement in the design of suspension system thereby achieving a better ride comfort when compared with the results of previous researchers. Journal: Int. J. of Operational Research Pages: 324-344 Issue: 3 Volume: 37 Year: 2020 Keywords: design optimisation; ABC algorithm; vehicle model; degree of freedom; DOF; suspension system; ride comfort. File-URL: http://www.inderscience.com/link.php?id=105442 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:3:p:324-344 Template-Type: ReDIF-Article 1.0 Author-Name: Srikant Gupta Author-X-Name-First: Srikant Author-X-Name-Last: Gupta Author-Name: Irfan Ali Author-X-Name-First: Irfan Author-X-Name-Last: Ali Author-Name: Aquil Ahmed Author-X-Name-First: Aquil Author-X-Name-Last: Ahmed Title: An extended multi-objective capacitated transportation problem with mixed constraints in fuzzy environment Abstract: In this paper, we study a multi-objective capacitated transportation problem (MOCTP) with mixed constraints. This paper is comprised of the modelling and optimisation of an MOCTP in a fuzzy environment in which some goals are fractional and some are linear. In real life application of the fuzzy goal programming (FGP) problem with multiple objectives, it is difficult for the decision maker(s) to determine the goal value of each objective precisely as the goal values are imprecise or uncertain. Also, we developed the concept of linearisation of fractional goal for solving the MOCTP. In this paper imprecision of the parameter is handled by the concept of fuzzy set theory by considering these parameters as a trapezoidal fuzzy number. <i>α</i>-cut approach is used to get the crisp value of the parameters. Numerical examples are used to illustrate the method for solving MOCTP. Journal: Int. J. of Operational Research Pages: 345-376 Issue: 3 Volume: 37 Year: 2020 Keywords: capacitated transportation problem; multi objective linear programming; multi-objective fractional programming; mixed constraints; trapezoidal fuzzy number; fuzzy goal programming; FGP. File-URL: http://www.inderscience.com/link.php?id=105443 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:3:p:345-376 Template-Type: ReDIF-Article 1.0 Author-Name: Sudipta Midya Author-X-Name-First: Sudipta Author-X-Name-Last: Midya Author-Name: Sankar Kumar Roy Author-X-Name-First: Sankar Kumar Author-X-Name-Last: Roy Title: Multi-objective fixed-charge transportation problem using rough programming Abstract: This paper analyses the multi-objective fixed-charge transportation problem (MOFCTP) using rough programming. Due to globalisation of market, the parameters of MOFCTP may not be defined precisely, so the parameters of the MOFCTP are treated as rough intervals. Expected value operator is used to convert rough MOFCTP to deterministic MOFCTP. Fuzzy programming method and linear weighted-sum method are used to obtain Pareto-optimal solution from deterministic MOFCTP. A comparative study is made between the obtained solutions extracted from the methods; and thereafter we perform a procedure to analyse the sensitive analysis of the parameters in MOFCTP. Finally, in order to show the applicability of our proposed study, an example on MOFCTP is included in this paper. Journal: Int. J. of Operational Research Pages: 377-395 Issue: 3 Volume: 37 Year: 2020 Keywords: fixed-charge transportation problem; FCTP; rough programming; fuzzy programming; multi-objective programming; Pareto-optimal solution. File-URL: http://www.inderscience.com/link.php?id=105444 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:3:p:377-395 Template-Type: ReDIF-Article 1.0 Author-Name: Liezl Van Eck Author-X-Name-First: Liezl Van Author-X-Name-Last: Eck Author-Name: Stephan E. Visagie Author-X-Name-First: Stephan E. Author-X-Name-Last: Visagie Title: On exact solution approaches for concave knapsack problems Abstract: This paper introduces five characteristics of concave knapsack problem (CKP) instances that influence computational times of algorithms. A dataset, based on these characteristics, is randomly generated and made available online for future studies and comparison of computational times. In this study the dataset is used to compare the computational performance of two integer programming formulations and four algorithms to solve CKPs. A novel algorithm (BLU) that combines the logic of dynamic programming and the Karush-Kuhn-Tucker necessary conditions for the CKP is also introduced. The computational times for the two integer programming formulations were too long and were thus excluded from the statistical analysis. Analysis of the computational times shows that algorithms are sensitive to different characteristics. Any algorithm, depending on the settings of the five characteristics, could win in terms of average computational time, but BLU outperforms the other algorithms over the widest range of settings for these characteristics. Journal: Int. J. of Operational Research Pages: 396-417 Issue: 3 Volume: 37 Year: 2020 Keywords: concave knapsack problem; CKP; branch-and-bound; dynamic programming; comparison of algorithms. File-URL: http://www.inderscience.com/link.php?id=105445 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:3:p:396-417 Template-Type: ReDIF-Article 1.0 Author-Name: P. Senthil Kumar Author-X-Name-First: P. Senthil Author-X-Name-Last: Kumar Title: Intuitionistic fuzzy zero point method for solving type-2 intuitionistic fuzzy transportation problem Abstract: In conventional transportation problem, supply, demand and costs are fixed crisp numbers. Therefore, in this situation, the decision maker (DM) can predict transportation cost exactly. On the contrary, in real world transportation problems the costs are in uncertain quantities with hesitation due to various factors like variation in rates of fuels, traffic jams, weather in hilly areas, etc. In such situations, the DM cannot predict transportation cost exactly and it will force the DM to hesitate. So, to counter these uncertainties, in this article, the author designed a transportation problem in which supplies, demands are crisp numbers and cost is intuitionistic fuzzy number. This type of problem is termed as type-2 intuitionistic fuzzy transportation problem (type-2 IFTP). Hence to deal with uncertainty and hesitation in transportation problem, intuitionistic fuzzy zero point method is proposed to find out optimal solution to the type-2 IFTP. Moreover, special kind of type-2 IFTP is proposed and its related theorems are proved. Finally, the ideas of the proposed method are illustrated with the help of numerical example which is followed by the results and discussion. Journal: Int. J. of Operational Research Pages: 418-451 Issue: 3 Volume: 37 Year: 2020 Keywords: intuitionistic fuzzy set; triangular intuitionistic fuzzy number; TIFN; trapezoidal intuitionistic fuzzy number; TrIFN; type-2 intuitionistic fuzzy transportation; intuitionistic fuzzy zero point method; optimal solution. File-URL: http://www.inderscience.com/link.php?id=105446 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:3:p:418-451 Template-Type: ReDIF-Article 1.0 Author-Name: Joaquim Jorge Vicente Author-X-Name-First: Joaquim Jorge Author-X-Name-Last: Vicente Author-Name: Susana Relvas Author-X-Name-First: Susana Author-X-Name-Last: Relvas Author-Name: Ana Paula Barbosa-Póvoa Author-X-Name-First: Ana Paula Author-X-Name-Last: Barbosa-Póvoa Title: Supply chain management under product demand and lead time uncertainty Abstract: This paper considers a multi-echelon inventory/distribution system formed by N-warehouses and M-retailers that manages a set of diverse products within a dynamic environment. Retailers are replenished from regional warehouses and these are supplied by a central distribution entity. Transshipment at both regional warehouses and retailers levels is allowed. A mixed integer linear programming model is developed, where product demand at the retailers is assumed to be unknown. The problem consists of determining the optimal reorder policy by defining the new concept of robust retailer order, which minimises the overall system cost, including ordering, holding in stock and in transit, transportation, transshipping and lost sales costs while guaranteeing service level. The proposed model is extended to address simultaneously uncertainty in both products demands and replenishment lead times. A case study based on a real retailer distribution chain is solved. Journal: Int. J. of Operational Research Pages: 453-478 Issue: 4 Volume: 37 Year: 2020 Keywords: distribution; inventory planning; uncertainty; scenario planning approach; mixed integer linear programming; MILP. File-URL: http://www.inderscience.com/link.php?id=105763 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:4:p:453-478 Template-Type: ReDIF-Article 1.0 Author-Name: Majid Forghani-Elahabad Author-X-Name-First: Majid Author-X-Name-Last: Forghani-Elahabad Author-Name: Nezam Mahdavi-Amiri Author-X-Name-First: Nezam Author-X-Name-Last: Mahdavi-Amiri Author-Name: Nelson Kagan Author-X-Name-First: Nelson Author-X-Name-Last: Kagan Title: On multi-state two separate minimal paths reliability problem with time and budget constraints Abstract: In a stochastic-flow network, a (<i>d</i>, <i>T</i>, <i>b</i>, <i>P</i><SUB align="right"><SMALL>1</SMALL></SUB>, <i>P</i><SUB align="right"><SMALL>2</SMALL></SUB>)-MP is a system state vector for which d units of flow can be transmitted through two separate minimal paths (SMPs) P1 and P2 simultaneously from a source node to a sink node satisfying time and budget limitations <i>T</i> and <i>b</i>, respectively. Problem of determining all the (<i>d</i>, <i>T</i>, <i>b</i>, <i>P</i><SUB align="right"><SMALL>1</SMALL></SUB>, <i>P</i><SUB align="right"><SMALL>2</SMALL></SUB>)-MPs, termed as the (<i>d</i>, <i>T</i>, <i>b</i>, <i>P</i><SUB align="right"><SMALL>1</SMALL></SUB>, <i>P</i><SUB align="right"><SMALL>2</SMALL></SUB>)-MP problem, has been attractive in reliability theory. Here, some new results are established for the problem. Using these results, a new algorithm is developed to find all the (<i>d</i>, <i>T</i>, <i>b</i>, <i>P</i><SUB align="right"><SMALL>1</SMALL></SUB>, <i>P</i><SUB align="right"><SMALL>2</SMALL></SUB>)-MPs, and its correctness is established. The algorithm is compared with a recently proposed one to show the practical efficiency of the algorithm. Journal: Int. J. of Operational Research Pages: 479-490 Issue: 4 Volume: 37 Year: 2020 Keywords: stochastic quickest path reliability problem; transmission time; budget constraint; minimal paths; MPs; (d, T, b, P1, P2)-MP. File-URL: http://www.inderscience.com/link.php?id=105764 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:4:p:479-490 Template-Type: ReDIF-Article 1.0 Author-Name: Minakshi Parida Author-X-Name-First: Minakshi Author-X-Name-Last: Parida Author-Name: Sunita Chand Author-X-Name-First: Sunita Author-X-Name-Last: Chand Title: On gH-differentiable harmonic invex fuzzy mappings and its applications Abstract: In this paper, harmonic invex (H-invex) and harmonic incave (H-incave) fuzzy mappings have been introduced by using the concept of gH-differentiability and many important results have been obtained related to pseudoinvex (pseudoincave), quasiinvex (quasiincave), H-preinvex (H-preincave), η-monotone, η-dissipative, pseudoinvex monotone and pseudoincave dissipative fuzzy mappings. The results obtained have been justified with suitable examples. Furthermore, gH-differentiable H-invex fuzzy mappings have also been applied to study the KKT conditions for harmonic invex fuzzy programming problem (HIFP), duality results and minmax problem. Journal: Int. J. of Operational Research Pages: 491-523 Issue: 4 Volume: 37 Year: 2020 Keywords: fuzzy optimisation; H-invex; H-incave; gH-differentiable fuzzy mappings; KKT conditions; duality results; minmax problem. File-URL: http://www.inderscience.com/link.php?id=105765 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:4:p:491-523 Template-Type: ReDIF-Article 1.0 Author-Name: J. Kathiresan Author-X-Name-First: J. Author-X-Name-Last: Kathiresan Author-Name: N. Anbazhagan Author-X-Name-First: N. Author-X-Name-Last: Anbazhagan Title: An inventory system with retrial demands, multiple vacations and two supply modes Abstract: This paper analyses a continuous review inventory system with single server, multiple vacations, Poisson demand, retrial demand, exponential distributed lead time and two supply modes for replenishment with one having a shorter lead time. To derive the stationary distribution of the system, we employ the Gaver's method. After computing various system performance measures, some cost minimisation numerical results are presented. Journal: Int. J. of Operational Research Pages: 524-548 Issue: 4 Volume: 37 Year: 2020 Keywords: continuous review inventory system; positive leadtime; retrial demand; multiple vacations; two supply modes; Poisson demand; single server; finite orbit; constant retrial policy; Markov process. File-URL: http://www.inderscience.com/link.php?id=105766 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:4:p:524-548 Template-Type: ReDIF-Article 1.0 Author-Name: A. Jayanand Author-X-Name-First: A. Author-X-Name-Last: Jayanand Title: A cooperative combined defense technique for jamming attack in MANET Abstract: Mobile ad hoc networks (MANET) consist of continuously mobile nodes in the network. Due to this dynamic nature of the network, new nodes keep joining the network and some nodes exit the network every now and then. As a result, keeping track of every node in the network is not possible. So, malicious nodes like jammers can easily enter the network and affect the efficiency of the network. Hence, in this paper, we develop a cooperative combined defense technique for detecting jamming attacks in the MANET by determining the presence of jammers in the network. This is achieved by combining several important factors like correlation coefficient, carrier sensing time, packet delivery ratio (PDR) and signal strength (SS). Then a trust model is derived for each node and updated based on these measured parameters. Each node collaboratively checks the updated trust values of a suspected node and detects the jamming attack. Simulation results show that the proposed technique improves the detection accuracy and packet delivery ratio. Journal: Int. J. of Operational Research Pages: 549-561 Issue: 4 Volume: 37 Year: 2020 Keywords: mobile ad hoc networks; MANET; packet delivery ratio; PDR; signal strength; jamming attack. File-URL: http://www.inderscience.com/link.php?id=105767 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:4:p:549-561 Template-Type: ReDIF-Article 1.0 Author-Name: Shruti Kapoor Author-X-Name-First: Shruti Author-X-Name-Last: Kapoor Author-Name: Selvamuthu Dharmaraja Author-X-Name-First: Selvamuthu Author-X-Name-Last: Dharmaraja Title: Steady state analysis of fluid queues driven by birth death processes with rational rates Abstract: Birth death processes with rational birth death rates have been studied by Maki (1976). This paper analyses the steady state behaviour of a fluid queue driven by a finite birth death process with rational birth and death rates. Two specific models are considered and closed form solutions are obtained for the equilibrium distribution of the buffer occupancy by finding the explicit eigenvalues of the underlying tridiagonal matrix. Numerical illustration is presented for different values of the size of the state space of the background process and for different values of the parameter involved. Journal: Int. J. of Operational Research Pages: 562-578 Issue: 4 Volume: 37 Year: 2020 Keywords: fluid queue; stationary distribution; eigenvalues; tridiagonal matrices. File-URL: http://www.inderscience.com/link.php?id=105768 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:4:p:562-578 Template-Type: ReDIF-Article 1.0 Author-Name: C. Venkataramanan Author-X-Name-First: C. Author-X-Name-Last: Venkataramanan Author-Name: S.M. Girirajkumar Author-X-Name-First: S.M. Author-X-Name-Last: Girirajkumar Title: Hierarchical MAC protocol with adaptive duty-cycle adjustment algorithm for wireless sensor network Abstract: In wireless sensor networks (WSNs), the existing routing algorithms causes increased energy utilisation and minimises the lifetime of the network. In order to conquer this problem, in this paper, an adaptive duty-cycle adjustment algorithm based on the traffic and channel condition is put forwarded. Initially, the node with higher weight value is chosen as cluster head, the value is calculated from residual energy and delay between the successive transmissions. After the cluster formation, the relay nodes are selected by their remaining battery energy and the channel state in the network for the data transmission. Based on the relay nodes found, the network traffic is controlled by the traffic adaptive duty-cycle. In this approach, the heads of each cluster collects traffic information from member nodes and computes appropriate duty cycle according to current traffic, and then the resulting duty cycle information conveyed to normal nodes. The node then executes the data transmission based on the duty cycle. Our results revealed that the proposed approach minimises the energy utilisation and enhances the network lifetime too. Journal: Int. J. of Operational Research Pages: 579-599 Issue: 4 Volume: 37 Year: 2020 Keywords: wireless sensor networks; MAC protocol; adaptive duty-cycle; hierarchical cluster; cluster head; energy utilisation; delay; channel state condition. File-URL: http://www.inderscience.com/link.php?id=105769 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:37:y:2020:i:4:p:579-599 Template-Type: ReDIF-Article 1.0 Author-Name: Akshay Kumar Author-X-Name-First: Akshay Author-X-Name-Last: Kumar Author-Name: S.B. Singh Author-X-Name-First: S.B. Author-X-Name-Last: Singh Author-Name: Mangey Ram Author-X-Name-First: Mangey Author-X-Name-Last: Ram Title: Systems reliability assessment using hesitant fuzzy set Abstract: The present study deals with fuzzy reliability evaluation series, parallel and linear (circular) consecutive <i>k-out-of-n</i>: F systems. Fuzzy reliability of series, parallel systems have been evaluated to help of hesitant fuzzy sets and triangular fuzzy number, whereas fuzzy reliability of linear (circular) consecutive <i>k-out-of-n</i>: F systems have been determined with the help of application of Weibull distribution and Markov process in comporting hesitant fuzzy sets and triangular fuzzy number. Numerical examples are also provided to demonstrate the effectiveness of the proposed approach. Journal: Int. J. of Operational Research Pages: 1-18 Issue: 1 Volume: 38 Year: 2020 Keywords: series system; parallel system; Weibull distribution; linear (circular) (k, n: F) system; hesitant fuzzy set; hesitant fuzzy weighted averaging operator. File-URL: http://www.inderscience.com/link.php?id=106357 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:1:p:1-18 Template-Type: ReDIF-Article 1.0 Author-Name: Harrison O. Amuji Author-X-Name-First: Harrison O. Author-X-Name-Last: Amuji Author-Name: Fidelis I. Ugwuowo Author-X-Name-First: Fidelis I. Author-X-Name-Last: Ugwuowo Author-Name: Walford I.E. Chukwu Author-X-Name-First: Walford I.E. Author-X-Name-Last: Chukwu Author-Name: Peter. I. Uche Author-X-Name-First: Peter. I. Author-X-Name-Last: Uche Title: A modified generalised inverse method for solving geometric programming problems with extended degrees of difficulties (K ≥ 0) Abstract: We have developed a new method of solving geometric programming problems with as many positive degrees of difficulties as possible. Geometric programming has no direct solution whenever its degrees of difficulties are greater than zero; this has hindered the development of geometric programming and discouraged so many researchers into the area. The indirect solution, which has been in existence, involves the conversion of geometric programming problems to linear programming, separable programming, augmented programming etc. These conversions make the beauty of geometric programming to be lost and also terminate the existence of geometric programming. The newly developed method (modified generalised inverse method) consistently produces global optimal solutions; satisfies the orthogonality and normality conditions; optimal objective function; and produce optimal primal and dual decision variables which satisfy the optimal objective function. The method was applied on some positive degrees of difficulty geometric programming problems and the results compare to the results from existing methods. The method was validated by some proposition; corollary and lemma. With this breakthrough, geometric programming problems can be modeled and solved without restrictions. Journal: Int. J. of Operational Research Pages: 19-30 Issue: 1 Volume: 38 Year: 2020 Keywords: exponent matrix; degree of difficulty; generalised inverse; primal decision variables; dual decision variables; objective function. File-URL: http://www.inderscience.com/link.php?id=106358 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:1:p:19-30 Template-Type: ReDIF-Article 1.0 Author-Name: Ashish Trivedi Author-X-Name-First: Ashish Author-X-Name-Last: Trivedi Author-Name: Amol Singh Author-X-Name-First: Amol Author-X-Name-Last: Singh Title: A multi-objective approach for locating temporary shelters under damage uncertainty Abstract: Every year, natural disasters such as earthquakes, hurricanes, landslides, etc. kill thousands of people and destroy habitats and assets worth millions-of-dollars. Choice of temporary shelter areas and subsequent relocation of homeless people play a crucial role in post-earthquake relief operations. This paper proposes a multi-objective location-relocation model based on goal programming approach considering uncertainties of damage to infrastructure due to earthquakes. The model considers multiple objectives of risk, number of sites, unmet demand and qualitative suitability of locations and generates solutions under different scenarios of damage. A numerical illustration is also presented to demonstrate the applicability of proposed approach in solving the decision problem. Journal: Int. J. of Operational Research Pages: 31-48 Issue: 1 Volume: 38 Year: 2020 Keywords: disaster; goal programming; humanitarian logistics; shelter site selection; uncertainty. File-URL: http://www.inderscience.com/link.php?id=106359 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:1:p:31-48 Template-Type: ReDIF-Article 1.0 Author-Name: Suchithra Rajendran Author-X-Name-First: Suchithra Author-X-Name-Last: Rajendran Author-Name: A. Ravi Ravindran Author-X-Name-First: A. Ravi Author-X-Name-Last: Ravindran Title: Multi-criteria approach for platelet inventory management in hospitals Abstract: In this paper, a multiple criteria approach is proposed for platelet inventory management in hospitals. It has been reported that about 20% of the total platelet collected is outdated due to the short shelf life of platelets and demand uncertainty resulting in severe shortage. A multiple criteria mathematical programming (MCMP) model is developed to minimise three criteria: platelet wastage, shortage, and procurement and holding cost. The MCMP problem is solved using three MCMP techniques; preemptive goal programming (PGP), non-preemptive goal programming (NPGP) and weighted objective methods (WOM). A case study is discussed by applying the model to the daily demand data of platelets. Sensitivity analysis is also performed to analyze the impact of goal priorities in the PGP model and weights in the NPGP model and WOM. Based on the policies obtained under PGP, NPGP and WOM methods, the hospital management can decide the most suitable inventory policy for implementation. From the results, it is recommended that preemptive goal programming technique can be used if few goals are extremely important or given very high priority compared to others and is recommended to use weighted moving average or non-preemptive goal programming techniques if equal importance is given to all the goals. Journal: Int. J. of Operational Research Pages: 49-69 Issue: 1 Volume: 38 Year: 2020 Keywords: platelet inventory management; multiple criteria mathematical programming; preemptive goal programming; non-preemptive goal programming; weighted objective methods; sensitivity analysis. File-URL: http://www.inderscience.com/link.php?id=106360 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:1:p:49-69 Template-Type: ReDIF-Article 1.0 Author-Name: Hanane Taffahi Author-X-Name-First: Hanane Author-X-Name-Last: Taffahi Author-Name: David Claudio Author-X-Name-First: David Author-X-Name-Last: Claudio Title: A comparative analysis between LINMAP, paired comparison method and naturalistic ranking in different data display contexts Abstract: This article presents a comparative analysis between two widely used decision-making methods, LINMAP and paired comparison method (PCM), using three different judging contexts. Decision makers ranked alternatives (for LINMAP) and criteria (for PCM) for contexts involving quantitative data only, qualitative data only, and a mix between the two. Attribute weights were calculated and final rankings of alternatives were deducted and compared to a naturalistic ranking of alternatives by the decision makers. LINMAP was found to be the closest match to a naturalistic decision-making. It was also found that incorporating qualitative data or a mixture between qualitative and quantitative data in multi-attribute decision-making problems was more consistent with the naturalistic ranking of alternatives. Journal: Int. J. of Operational Research Pages: 70-81 Issue: 1 Volume: 38 Year: 2020 Keywords: LINMAP; paired comparison method; PCM; naturalistic ranking; quantitative data; qualitative data; multi-attribute decision-making; MADM. File-URL: http://www.inderscience.com/link.php?id=106361 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:1:p:70-81 Template-Type: ReDIF-Article 1.0 Author-Name: Charan Jeet Singh Author-X-Name-First: Charan Jeet Author-X-Name-Last: Singh Author-Name: Sandeep Kaur Author-X-Name-First: Sandeep Author-X-Name-Last: Kaur Author-Name: Madhu Jain Author-X-Name-First: Madhu Author-X-Name-Last: Jain Title: Unreliable server retrial G-queue with bulk arrival, optional additional service and delayed repair Abstract: The retrial bulk arrival queue with unreliable server and negative customers is considered. On arrival of the group of customers, one of the customers gets the service immediately if the server is idle and other customers join the retrial orbit. There is a provision to opt additional service after completion of the essential service of the customers. The server may fail due to arrival of negative customers during any stage of the service. After completion of the service, the customer may again join the queue as a feedback customer to get another regular/optional service or depart from the system. The non-persistent (impatient) phenomenon also occurs because of the delayed in repair/repair time of the failed server. By using the supplementary variable approach, various measures of queueing and reliability characteristics are analysed. To facilitate the comparative study of the performance metrics of the system, the maximum entropy principle is used. The numerical results for various performance indices and optimal cost are obtained. Journal: Int. J. of Operational Research Pages: 82-111 Issue: 1 Volume: 38 Year: 2020 Keywords: unreliable server; retrial queue; non-persistent; supplementary variable; feedback; optional service. File-URL: http://www.inderscience.com/link.php?id=106362 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:1:p:82-111 Template-Type: ReDIF-Article 1.0 Author-Name: Babak H. Tabrizi Author-X-Name-First: Babak H. Author-X-Name-Last: Tabrizi Author-Name: Masoud Rabbani Author-X-Name-First: Masoud Author-X-Name-Last: Rabbani Title: A graph theoretic-based approach to distribution network planning with routes interaction regarding the fix-charge transportation problem Abstract: This paper aims to take distribution network planning problem into consideration, since a well-configured network can provide an appropriate platform for effective and efficient management of the set. The fix-charge transportation approach is addressed here to account for the problem. Hence, a nonlinear mixed-integer programming model is proposed to minimise the configuration costs, in addition to the routes interaction consideration. Likewise, a graph theoretic-based methodology, i.e., the minimum spanning tree concept, is pursued by the Prüfer number representation to deal with trees coding and decoding procedure. Due to the problem solution complexity, genetic and simulated annealing algorithms are applied to deal with large-sized problems. Moreover, a robust tuning is utilised to the key parameters of the solution methodologies using the Taguchi method. Finally, some numerical examples are developed in order to compare the performance of the solution approaches with that of CPLEX. Journal: Int. J. of Operational Research Pages: 112-136 Issue: 1 Volume: 38 Year: 2020 Keywords: distribution network configuration; spanning tree; genetic algorithm; simulated annealing algorithm. File-URL: http://www.inderscience.com/link.php?id=106363 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:1:p:112-136 Template-Type: ReDIF-Article 1.0 Author-Name: Miltiadis Chalikias Author-X-Name-First: Miltiadis Author-X-Name-Last: Chalikias Author-Name: Panagiota Lalou Author-X-Name-First: Panagiota Author-X-Name-Last: Lalou Author-Name: Michalis Skordoulis Author-X-Name-First: Michalis Author-X-Name-Last: Skordoulis Author-Name: Perikles Papadopoulos Author-X-Name-First: Perikles Author-X-Name-Last: Papadopoulos Author-Name: Stavros Fatouros Author-X-Name-First: Stavros Author-X-Name-Last: Fatouros Title: Bank oligopoly competition analysis using a differential equations model Abstract: The purpose of this paper is to propose a model of differential equations that will be able to be applied in a bank oligopoly competition case. The differential equations model will be based on Lanchester's combat model, a well-known mathematical theory of war. Due to the fact that an oligopoly of four banks will be examined, the proposed model will consist of a 4x4 differential equations system. Many researchers have already concluded that mathematical theories of war models can be successfully applied to business cases as there are many similarities between the battle fields and the business competition. Since the proposed model's predictions concern the deposits evolution, this model can contribute in the analysis of the competition between the four major banks in Greece. The statistical analyses carried out confirm the model's good fit. Journal: Int. J. of Operational Research Pages: 137-145 Issue: 1 Volume: 38 Year: 2020 Keywords: operations research; Lanchester combat model; differential equations; oligopoly; bank competition; banking sector. File-URL: http://www.inderscience.com/link.php?id=106364 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:1:p:137-145 Template-Type: ReDIF-Article 1.0 Author-Name: Imen Chaouch Author-X-Name-First: Imen Author-X-Name-Last: Chaouch Author-Name: Olfa Belkahla Driss Author-X-Name-First: Olfa Belkahla Author-X-Name-Last: Driss Author-Name: Khaled Ghedira Author-X-Name-First: Khaled Author-X-Name-Last: Ghedira Title: A review of job shop scheduling problems in multi-factories Abstract: The distributed job shop scheduling problem (DJSP) deals with the assignment of jobs to factories geographically distributed and with determining a good operation schedule of each factory. It is one of the well-known NP-hard combinatorial optimisation problem to solve optimally. In the last two decades, the problem has captured the interest of a number of researchers and therefore various methods have been employed to study this problem. In this paper, we first present an overview of pioneer studies conducted on solving distributed job shop scheduling problems and a classification of the employed techniques is given. Then, depth analysis of the outcome of existing literature is presented. Journal: Int. J. of Operational Research Pages: 147-165 Issue: 2 Volume: 38 Year: 2020 Keywords: distributed scheduling; job shop; flexible job shop; optimisation method; survey. File-URL: http://www.inderscience.com/link.php?id=107068 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:2:p:147-165 Template-Type: ReDIF-Article 1.0 Author-Name: Shantanu Shankar Bagchi Author-X-Name-First: Shantanu Shankar Author-X-Name-Last: Bagchi Author-Name: A.K. Rao Author-X-Name-First: A.K. Author-X-Name-Last: Rao Title: Optimal sourcing policies for single and multiple period scenarios Abstract: Determining the optimum number of suppliers and the optimum quantities to order from each of them is a critical problem for any supply chain. The objective of this paper is to identify the optimal sourcing policy of a retailer for the single and multi-period context when the firm can source its order to multiple suppliers along with a back-up supplier for the emergency situations. The expected total profit is mathematically modelled for single and multi-period scenarios. The optimal sourcing policy is obtained by maximising the expected total profit with respect to the order quantities. Closed form solution is obtained for uniformly distributed demand for both single and multi-period scenarios. It is observed that the multi-period solution is less sensitive compared to the single-period solution. Also it is found that it is optimal for the firm to lessen the amount of supplier diversification in case of planning for multiple periods. Journal: Int. J. of Operational Research Pages: 166-192 Issue: 2 Volume: 38 Year: 2020 Keywords: sourcing; supplier yield; stochastic model; demand uncertainty; supply uncertainty; optimisation. File-URL: http://www.inderscience.com/link.php?id=107069 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:2:p:166-192 Template-Type: ReDIF-Article 1.0 Author-Name: T.G. Pradeepmon Author-X-Name-First: T.G. Author-X-Name-Last: Pradeepmon Author-Name: Vinay V. Panicker Author-X-Name-First: Vinay V. Author-X-Name-Last: Panicker Author-Name: R. Sridharan Author-X-Name-First: R. Author-X-Name-Last: Sridharan Title: Genetic algorithm for quadratic assignment problems: application of Taguchi method for optimisation Abstract: Quadratic assignment problems (QAPs) are the hardest of combinatorial optimisation problems, with some problems of sizes of the order of 30 still remaining unsolved optimally. Solving QAPs with exact optimisation methods is cumbersome and hence, the use of non-conventional optimisation methods is recommended. Genetic algorithm (GA) being one of the most popular evolutionary algorithms is an appropriate choice for solving QAPs. The methods of operations used in GA influence the solution quality and thus, an optimal combination of parameters and operators are required for the efficient implementation of the algorithm. In this paper, the Taguchi's design of experiments method is used to find the best parameter combination and the best performing combination of operations for GA. The GA thus obtained by incorporating the selected parameter values and operators is then used for solving the QAPs taken from the QAP library. For many of the problems, it is found that the results obtained are within one percentage deviation from the best-known solutions. Journal: Int. J. of Operational Research Pages: 193-220 Issue: 2 Volume: 38 Year: 2020 Keywords: quadratic assignment problem; QAPs; genetic algorithms; Taguchi's design of experiments method; optimisation of operations and parameters. File-URL: http://www.inderscience.com/link.php?id=107070 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:2:p:193-220 Template-Type: ReDIF-Article 1.0 Author-Name: N. Zeelanbasha Author-X-Name-First: N. Author-X-Name-Last: Zeelanbasha Author-Name: V. Senthil Author-X-Name-First: V. Author-X-Name-Last: Senthil Author-Name: G. Mahesh Author-X-Name-First: G. Author-X-Name-Last: Mahesh Title: A hybrid approach of NSGA-II and TOPSIS for minimising vibration and surface roughness in machining process Abstract: Increasing vibration amplitude during end milling process can seriously affect the life of end mills and reduces surface finish. Spindle and worktable vibration has a significant influence on surface quality of machined components. This paper confronts and investigates the effect of machining and geometrical parameters (spindle speed, feed rate, axial depth of cut, radial depth of cut and radial rake angle) on spindle and worktable vibration in terms of acceleration amplitude and surface roughness. Experiments were conducted on aluminium alloy 6061-T6 with high-speed steel (HSS) end mill cutter based on the central composite design (CCD). Response surface methodology (RSM) was used to develop the predictive models and the adequacy of the models were verified using analysis of variance (ANOVA). Non-dominated sorting of genetic algorithm (NSGA-II) was adopted to solve the multi objective optimisation problem and the optimised results were resulted with a set of Pareto-optimal solutions. The multi criteria decision making method (MCDM) such as technique for order preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP) were designed to rank the Pareto optimal solutions based on response of closeness coefficient values. Journal: Int. J. of Operational Research Pages: 221-254 Issue: 2 Volume: 38 Year: 2020 Keywords: aluminium alloy; decision making; end milling; machining; NSGA-II; optimisation; prediction; TOPSIS; vibration; surface roughness. File-URL: http://www.inderscience.com/link.php?id=107071 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:2:p:221-254 Template-Type: ReDIF-Article 1.0 Author-Name: M. Birasnav Author-X-Name-First: M. Author-X-Name-Last: Birasnav Author-Name: S. Kalaivanan Author-X-Name-First: S. Author-X-Name-Last: Kalaivanan Author-Name: A. Ramesh Author-X-Name-First: A. Author-X-Name-Last: Ramesh Author-Name: Rajendra Tibrewala Author-X-Name-First: Rajendra Author-X-Name-Last: Tibrewala Title: Routing vehicles through cross-docking facility for third party logistics service providers Abstract: This study focuses on a specialised vehicle routing problem (VRP) to transport matchboxes from manufacturing companies to retailers through a cross-dock (cross-docking facility) operated by a third party logistics service provider. Three processes (unloading, consolidating, and loading) are carried out at a cross-dock for completely avoiding or keeping inventory for a very short time. The specialised VRP, addressed in this paper, consists of multiple suppliers (each supplier can produce different brands of products for any number of customers) and multiple customers (each customer can receive orders from any number of suppliers). A mixed integer linear programming model has been developed to solve this kind of <i>NP-hard</i> problem. The objective of this model is to minimise total cost incurred in picking up and transporting the matchboxes from the manufacturers to cross-dock, consolidating matchboxes at cross-dock, and in transporting and delivering the matchboxes to the customers. This study also proposes an effective heuristic procedure to solve the same problem and compares the solution obtained using the heuristic procedure to the optimal solution obtained using the exact method. The findings show that the heuristic method, proposed by us, generates near optimum solutions using significantly less computational time than the exact method. Journal: Int. J. of Operational Research Pages: 255-277 Issue: 2 Volume: 38 Year: 2020 Keywords: vehicle routing; cross-docking; NP-hard; heuristic; logistics service provider; consolidating; multiple suppliers; multiple customers. File-URL: http://www.inderscience.com/link.php?id=107072 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:2:p:255-277 Template-Type: ReDIF-Article 1.0 Author-Name: Chee Keong Ch'ng Author-X-Name-First: Chee Keong Author-X-Name-Last: Ch'ng Author-Name: Nor Idayu Mahat Author-X-Name-First: Nor Idayu Author-X-Name-Last: Mahat Title: Winsorize tree algorithm for handling outlier in classification problem Abstract: Classification and regression tree (CART) has been widely used nowadays for providing users supports in classification and prediction. However, having outlier in database is inevitable and could affect the size and accuracy of the tree. Negligence in handling the outlier could affect the splitting point which yields to bias and inaccurate tree. In this paper, we propose a winsorize tree algorithm for detecting and handling the outlier before calculating gini index measurement in all non-terminal nodes. As such, the constructed tree will grow without the necessity to be pruned. For evaluation, the proposed approach was compared to classical tree and pruned tree. The results obtained from seven real datasets indicate that the proposed winsorize tree performs as good as or even better compare to the other investigated trees. Journal: Int. J. of Operational Research Pages: 278-293 Issue: 2 Volume: 38 Year: 2020 Keywords: winsorize tree algorithm; gini index; error rate; classification; outlier; classification and regression tree; winsorized tree. File-URL: http://www.inderscience.com/link.php?id=107073 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:2:p:278-293 Template-Type: ReDIF-Article 1.0 Author-Name: Ruilin Ouyang Author-X-Name-First: Ruilin Author-X-Name-Last: Ouyang Author-Name: Tasnim Ibn Faiz Author-X-Name-First: Tasnim Ibn Author-X-Name-Last: Faiz Author-Name: Md. Noor-E-Alam Author-X-Name-First: Md. Author-X-Name-Last: Noor-E-Alam Title: Location-allocation models for healthcare facilities with long-term demand Abstract: Healthcare facility location decisions are of great importance due to their impact on direct and social cost of people's well-being in a region. Optimal location decisions considering only current demand may become suboptimal as demand distribution changes. Considering future demand realisations in the decision making process can ensure long-term optimality. We present three mathematical models which follow grid-based location approach, and consider current and future demands in providing optimal location-allocation decisions. The first model considers allocations of present and future patients only to the nearest facilities. The second model allows patients to travel to facilities within allowable distance. The third model allows allocation of patients from one location to multiple facilities. The models are implemented with AMPL and numerical instances are solved with the CPLEX solver. Results show that the models are capable of solving medium size problems and the third model performs better in providing high quality solutions. Journal: Int. J. of Operational Research Pages: 295-320 Issue: 3 Volume: 38 Year: 2020 Keywords: healthcare facility location; grid-based location problem; long-term location decision; integer programming. File-URL: http://www.inderscience.com/link.php?id=107531 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:3:p:295-320 Template-Type: ReDIF-Article 1.0 Author-Name: Rahul Kumar Author-X-Name-First: Rahul Author-X-Name-Last: Kumar Author-Name: Pradip Kumar Bala Author-X-Name-First: Pradip Kumar Author-X-Name-Last: Bala Author-Name: Shubhadeep Mukherjee Author-X-Name-First: Shubhadeep Author-X-Name-Last: Mukherjee Title: Improving recommendation quality by identifying more similar neighbours in a collaborative filtering mechanism Abstract: Recommender systems (RS) act as an information filtering technology to ease the decision-making process of online consumers. Of all the known recommendation techniques, collaborative filtering (CF) remains the most popular. CF mechanism is based on the principle of word-of-mouth communication between like-minded users who share similar historical rating preferences for a common set of items. Traditionally, only those like-minded or similar users of the given user are selected as neighbours who have rated the item under consideration. Resultantly, the similarity strength of neighbours deteriorates as the most similar users may not have rated that item. This paper proposes a new approach for neighbourhood formation by selecting more similar neighbours who have not necessarily rated the item under consideration. Owing to data sparsity, most of the selected neighbours have missing ratings which are predicted using a unique algorithm adopting item based regression. The efficacy of the proposed approach remains superior over existing methods. Journal: Int. J. of Operational Research Pages: 321-342 Issue: 3 Volume: 38 Year: 2020 Keywords: collaborative filtering; recommender systems; similarity coefficient; true neighbours; prediction algorithm. File-URL: http://www.inderscience.com/link.php?id=107532 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:3:p:321-342 Template-Type: ReDIF-Article 1.0 Author-Name: Mohammed Chennoufi Author-X-Name-First: Mohammed Author-X-Name-Last: Chennoufi Author-Name: Fatima Bendella Author-X-Name-First: Fatima Author-X-Name-Last: Bendella Author-Name: Maroua Bouzid Author-X-Name-First: Maroua Author-X-Name-Last: Bouzid Title: Best A* discovery for multi agents planning Abstract: This paper proposes a new approach for multi-agent planning and decision support. The conventional algorithms such as Dijkstra, A* cannot solve complex problems with spatio-temporal constraints. So we are interested in developing a new strategy for the best path based on BDI agents for an emergency evacuation problem of a population crowd, besides the study of the macroscopic behaviour emerging from simple interactions between agents by decreasing the evacuation time which is a challenge and a very complex task. Multi-agent systems are well suited to modelling such systems. The idea is to make a two-dimensional modelling of the environment as a quadtree graph and an hybrid architecture: A* search from the node, where the individual is located to direct it to the best exit node while adding physiological factors to this research, a robust method for collision avoidance and decision support to help the agent will replace the initial destination with anew one. Our model is implemented and tested with java and Netlogo 5.2.1 platform. Journal: Int. J. of Operational Research Pages: 343-363 Issue: 3 Volume: 38 Year: 2020 Keywords: complex system; A*; multi-agent systems; MAS; crowd; path; decision support; planning; evacuation; simulation; emergence. File-URL: http://www.inderscience.com/link.php?id=107533 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:3:p:343-363 Template-Type: ReDIF-Article 1.0 Author-Name: André Martins Author-X-Name-First: André Author-X-Name-Last: Martins Author-Name: Peter F. Wanke Author-X-Name-First: Peter F. Author-X-Name-Last: Wanke Author-Name: Henrique L. Corrêa Author-X-Name-First: Henrique L. Author-X-Name-Last: Corrêa Title: Evaluation of ethanol multimodal transport logistics: a case in Brazil Abstract: This paper evaluates a large ethanol multimodal logistics system in Brazil. This system conducts ethanol logistics activities using pipelines and waterways to supply Brazil's internal and export markets. A transhipment model is used for the treatment of logistic flows. A linear programming model was developed to determine the transhipment and replenishment flows from more than 400 ethanol plants to more than 70 terminals and distribution centres. We found that optimal results occur when pipeline and waterway systems reach full capacity by taking volume from road transportation on long distances, suggesting that these options have the potential to make the ethanol logistics in Brazil more efficient and competitive in the future. Journal: Int. J. of Operational Research Pages: 364-391 Issue: 3 Volume: 38 Year: 2020 Keywords: ethanol; transhipment; pipeline; waterways; linear programming. File-URL: http://www.inderscience.com/link.php?id=107534 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:3:p:364-391 Template-Type: ReDIF-Article 1.0 Author-Name: S.R. Singh Author-X-Name-First: S.R. Author-X-Name-Last: Singh Author-Name: Swati Sharma Author-X-Name-First: Swati Author-X-Name-Last: Sharma Author-Name: Mohit Kumar Author-X-Name-First: Mohit Author-X-Name-Last: Kumar Title: A reverse logistics model for decaying items with variable production and remanufacturing incorporating learning effects Abstract: In order to meet environmental concerns/regulations, suppliers often endeavour to recover the residual value of their used products through remanufacturing. In this research article, an integrated production and remanufacturing inventory model for a single supplier and a single buyer is presented. There is one production and one remanufacturing cycle for the supplier while multiple batches are considered for the buyer. Demand rate for the supplier and buyer is taken a linearly increasing function of time. It is presumed that production, remanufacturing and returned rates are demand dependent and items deteriorate while they are kept in storage. This model also incorporates the effect of learning in ordering cost, holding cost, deteriorating cost and purchasing cost for the buyer as these costs reduce cycle by cycle due to learning effect from the previous cycle. The numerical examples, sensitively analysis and graphical illustrations are given to illustrate the proposed model. Journal: Int. J. of Operational Research Pages: 422-448 Issue: 3 Volume: 38 Year: 2020 Keywords: reverse logistics; inventory model; deterioration; variable production and remanufacturing; learning effects. File-URL: http://www.inderscience.com/link.php?id=107536 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:3:p:422-448 Template-Type: ReDIF-Article 1.0 Author-Name: Sunan Klinmalee Author-X-Name-First: Sunan Author-X-Name-Last: Klinmalee Author-Name: Thanakorn Naenna Author-X-Name-First: Thanakorn Author-X-Name-Last: Naenna Author-Name: Chirawat Woarawichai Author-X-Name-First: Chirawat Author-X-Name-Last: Woarawichai Title: Application of a genetic algorithm for multi-item inventory lot-sizing with supplier selection under quantity discount and lead time Abstract: This study presents an application of genetic algorithm (GA) for solving the multi-item inventory lot-sizing problem with supplier selection under discounts and lead time constraints. A mixed-integer linear programming (MILP) model is developed for proposed problem. To solve the problem, a genetic algorithm (GA) with two additional operations is proposed for handling the effect of the problem size. An adaptor for adjusting a chromosome data before the evaluation process and a penalty step for deterring an infeasible solution are developed. Finally, numerical examples are generated to evaluate the performance of the proposed GA, and the comparison with MILP approach about the solution quality and time is presented. Journal: Int. J. of Operational Research Pages: 403-421 Issue: 3 Volume: 38 Year: 2020 Keywords: genetic algorithm; GA; inventory lot-sizing; supplier selection; lead time; quantity discount; mixed-integer programming. File-URL: http://www.inderscience.com/link.php?id=107540 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:3:p:403-421 Template-Type: ReDIF-Article 1.0 Author-Name: Maged G. Iskander Author-X-Name-First: Maged G. Author-X-Name-Last: Iskander Title: A suggested method for solving capacitated location problems under fuzzy environment Abstract: In this paper, a new approach for solving fuzzy capacitated location problems is proposed. Both the capacity and the demand constraints are considered fuzzy while the objective function is not. A membership function is defined for the non-fuzzy objective function to convert it to a fuzzy one. The <i>α</i>- cut is used for the membership functions. The max-min approach is utilised within the proposed method. The models which are in the form of mixed zero-one nonlinear programs are transformed to their equivalent linear ones. Four mixed zero-one linear programs are required to be sequentially solved. The solution of the fourth program represents the ultimate optimal solution of the problem. The suggested approach is illustrated by a numerical example. Journal: Int. J. of Operational Research Pages: 392-402 Issue: 3 Volume: 38 Year: 2020 Keywords: fuzzy programming; fuzzy capacitated location problem; max-min approach; Chang's linearisation approach; mixed zero-one programs. File-URL: http://www.inderscience.com/link.php?id=107541 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:3:p:392-402 Template-Type: ReDIF-Article 1.0 Author-Name: Mustapha Hrouga Author-X-Name-First: Mustapha Author-X-Name-Last: Hrouga Author-Name: Matthieu Godichaud Author-X-Name-First: Matthieu Author-X-Name-Last: Godichaud Author-Name: Lionel Amodeo Author-X-Name-First: Lionel Author-X-Name-Last: Amodeo Title: Heuristics for disassembly lot sizing problem with lost sales Abstract: Disassembly is a major activity performed in treatment and recovery facilities and is the most important precedence of product and recovery part. This paper focus on single-item disassembly lot sizing problem with lost sales, we propose an optimisation approach to minimise the set-up costs and inventory costs in a first time and in second time we include lost sales costs. To this end, we propose three most well-known heuristic approaches for the single-item disassembly lot sizing problem with lost sales: silver meal (SM), part period balancing (PPB) and least unit cost (LUC). Results show that the heuristics used in the classical lot sizing problem can be also used to solve the disassembly lot sizing problem with lost sales, especially for small and medium instances. Results also show that can trust the proposed heuristics as a solution methodology to solve disassembly lost sizing without and with lost sales for larger instances. Journal: Int. J. of Operational Research Pages: 449-476 Issue: 4 Volume: 38 Year: 2020 Keywords: disassembly planning; lot-sizing; reverse logistics; lost sales; operational research; optimisation. File-URL: http://www.inderscience.com/link.php?id=108021 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:4:p:449-476 Template-Type: ReDIF-Article 1.0 Author-Name: S. Gunasekaran Author-X-Name-First: S. Author-X-Name-Last: Gunasekaran Author-Name: R. Maheswar Author-X-Name-First: R. Author-X-Name-Last: Maheswar Title: Hybrid BBO-PSO-based extreme learning machine neural network model for mitigation of harmonic distortions in micro grids Abstract: Microgrid tends to be the cluster of some of the renewable energy sources. The most important research area in the power distribution system side is the improvement in the quality of power delivered to the end users. This paper focuses on enhancing the power quality of the microgrid system; shunt active power filters (SAPF) is employed at the distribution side and to design an appropriate controller that achieves a better compensation for the considered SAPF. It is to be noted that the compensation methodology is dependent on the regulation process of the DC-link voltage. Traditionally, this regulation process is carried out employing a closed loop proportional-integral controller. In this paper, a hybrid biogeography-based optimisation – particle swarm optimization-based extreme learning machine neural network model is proposed to design the compensation for the SAPF and to mitigate the harmonics so that effective power gets delivered through the grid. Journal: Int. J. of Operational Research Pages: 507-524 Issue: 4 Volume: 38 Year: 2020 Keywords: microgrid; shunt active power filter; SAPF; power quality; harmonic mitigation; biogeography-based optimisation; BBO; particle swarm optimisation; PSO; extreme learning machine neural networks. File-URL: http://www.inderscience.com/link.php?id=108022 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:4:p:507-524 Template-Type: ReDIF-Article 1.0 Author-Name: N. Mohan Author-X-Name-First: N. Author-X-Name-Last: Mohan Title: Interference reduction using particle swarm optimisation in MIMO-WCDMA multicellular networks Abstract: In this paper, particle swarm optimisation (PSO) algorithm based interference reduction is proposed in multiple input multiple output (MIMO) using wide-band code division multiple access (WCDMA). During transmission MIMO network may get interfered by some interference such as co channel interference and adjacent channel interference. To reduce these interferences many algorithms have been proposed in previous research. Further improve the performance of the MIMO-WCDMA network and reduce the bit error rate (BER) an optimised algorithm is proposed. Simulation results of this paper show that bit error rate (BER) is reduced and also throughput of the network also improved. Journal: Int. J. of Operational Research Pages: 477-492 Issue: 4 Volume: 38 Year: 2020 Keywords: particle swarm optimisation; PSO; multiple input multiple output; MIMO; wide-band code division multiple access; WCDMA; bit error rate; BER. File-URL: http://www.inderscience.com/link.php?id=108023 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:4:p:477-492 Template-Type: ReDIF-Article 1.0 Author-Name: M.R. Senkumar Author-X-Name-First: M.R. Author-X-Name-Last: Senkumar Author-Name: K. Chitra Author-X-Name-First: K. Author-X-Name-Last: Chitra Author-Name: C. Selvakumar Author-X-Name-First: C. Author-X-Name-Last: Selvakumar Title: Blocking probability-based admission control technique for QoS provisioning in WDM networks Abstract: In this paper, we have proposed a blocking probability-based admission control technique for QoS provisioning on in WDM networks, for this, we estimate the blocking probability for an arriving connection request. The probability that there is at least one free wavelength at the specified book-ahead time that remains idle for the whole connection duration. Next to this an admission control scheme used in each group for deterministic QoS provisioning. The admission control scheme has its root from network calculus which can derive deterministic bounds on throughput and delay rather than statistical averages. Along with the delay metric, the blocking probability is also considered as the main constraints for admission control. The scheme allocates the aggregate token bucket for each class of traffic based on its bandwidth share. Journal: Int. J. of Operational Research Pages: 493-506 Issue: 4 Volume: 38 Year: 2020 Keywords: WDM networks; quality of service; QoS; blocking probability. File-URL: http://www.inderscience.com/link.php?id=108024 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:4:p:493-506 Template-Type: ReDIF-Article 1.0 Author-Name: Yong Joo Lee Author-X-Name-First: Yong Joo Author-X-Name-Last: Lee Author-Name: Seong-Jong Joo Author-X-Name-First: Seong-Jong Author-X-Name-Last: Joo Author-Name: Taewon Hwang Author-X-Name-First: Taewon Author-X-Name-Last: Hwang Title: An analysis of Korean bank performance using chance-constrained data envelopment analysis Abstract: For measuring the performance of firms using data envelopment analysis (DEA), many studies assume that inputs and outputs are deterministic. For example, key indicators for financial institutes such as assets, deposits, number of employees and profits vary over time. Nonetheless, researchers take snapshots of these numbers and analyse them for performance measurement and benchmarking. Similarly, it is not an exception for the studies with DEA for Korean financial institutes. We allow inputs and/or outputs to be stochastic and analyse the comparative performance of Korean banks. We found that large or top five banks were inconsistent sensitivity on the variability of inputs and/or outputs across models. The contributions of our study include demonstrating DEA analysis using stochastic inputs and outputs for the Korean banks and providing realistic insights to the managers of the banks. Journal: Int. J. of Operational Research Pages: 525-543 Issue: 4 Volume: 38 Year: 2020 Keywords: performance measurement; benchmarking; data envelopment analysis; DEA; stochastic variables; Korean banks; chance constrained DEA. File-URL: http://www.inderscience.com/link.php?id=108025 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:4:p:525-543 Template-Type: ReDIF-Article 1.0 Author-Name: J. Jeha Author-X-Name-First: J. Author-X-Name-Last: Jeha Author-Name: S. Charles Raja Author-X-Name-First: S. Charles Author-X-Name-Last: Raja Title: ABC algorithm for estimation of dynamic parameters in radial power system transfer path Abstract: In this paper, the artificial bee colony algorithm (ABC) is used to predict the stability of the power system and is evaluated the aggregated machine reactance and inertias in the transfer path. The proposed method is used for estimating the dynamic parameters of the aggregated machines for each area utilising the amplitudes of voltage oscillations measured at any three intermediate points on the transfer path. Two types of voltage control equipment are considered, namely, a static var compensator (SVC) and a thyristor controlled series capacitor (TCSC) including the purpose of voltage support and reducing the disturbance in the system. The proposed methods employ bus voltage phasor data at several buses including the voltage control bus and the line currents on the power transfer path. Here, the three phase fault is applied in the power system. Based on the estimation, the dynamics of the power system is improved and the proposed strategy is utilised for improving the overall dynamic security. The proposed technique is implemented in MATLAB/simulink working platform and the output performance is evaluated and compared with the existing methods such as without facts devices, SVC based controller and genetic algorithm (GA) based TCSC controller respectively. Journal: Int. J. of Operational Research Pages: 544-569 Issue: 4 Volume: 38 Year: 2020 Keywords: dynamic parameters; voltage; thyristor controlled series capacitor; TCSC; static var compensator; SVC; reactance; inertia; ABC and GA. File-URL: http://www.inderscience.com/link.php?id=108026 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:4:p:544-569 Template-Type: ReDIF-Article 1.0 Author-Name: Francesco Zammori Author-X-Name-First: Francesco Author-X-Name-Last: Zammori Title: A continuous review policy based on the stock diffusion theory: analysis and insights via Monte-Carlo simulation Abstract: The stock diffusion theory (SDT) is a mathematical model, based on the Fokker Planck equation, that makes it possible to accurately estimate stock-out probability, even in case of highly heteroscedastic demand. The paper shows how the SDT can be exploited to formulate an innovative continuous review policy, which can be effectively used for inventory management. Since the model needs, as input, the trend of the mean <i>μ</i>(<i>t</i>) and that of the variance <i>σ</i><SUP align="right"><SMALL>2</SMALL></SUP>(<i>t</i>) of the demand, the paper also introduces two alternative (and robust) ways to estimate these functions, starting from the time series of the demand. Lastly, analysis of variance, based on an extensive Monte-Carlo simulation, is performed to compare the proposed approach with respect to a set of standard continuous review policies taken as benchmark. Results confirm the robustness of the proposed policy and its applicability in many practical cases. Journal: Int. J. of Operational Research Pages: 570-598 Issue: 4 Volume: 38 Year: 2020 Keywords: continuous review policy; inventory management; Monte-Carlo simulation; stock diffusion theory. File-URL: http://www.inderscience.com/link.php?id=108027 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:38:y:2020:i:4:p:570-598 Template-Type: ReDIF-Article 1.0 Author-Name: Venkatachalam Manjula Author-X-Name-First: Venkatachalam Author-X-Name-Last: Manjula Author-Name: Ahamed Khan Mahabub Basha Author-X-Name-First: Ahamed Khan Mahabub Author-X-Name-Last: Basha Title: Adaptive technique for transient stability constraints optimal power flow Abstract: This document explains about an adaptive method for optimal power flow (OPF) of the power system, which is depending on the transient constancy restraints. The adaptive method is the mixture of both Cuckoo Search (CS) algorithm and artificial neural network (ANN). The innovative anticipated adaptive method is extremely flexible in nonlinear loads, suitable for user interface and logical reasoning, and allowing controlling formats. In the predefined generator, the CS algorithm optimises the generator arrangements by the load demand. The foremost intention of the CS algorithm is to reduce the fuel cost and emission cost. The obtainable ANN method is mainly used to develop the levy flight searching activities of the CS algorithm. The levy flight parameters are generally used to meet of the requirements the ANN, which envisage the precise consequences at the testing time. The anticipated adaptive method is executed in the MATLAB/Simulink platform and the efficiency of the anticipated procedure is investigated by the comparison analysis. Journal: Int. J. of Operational Research Pages: 1-23 Issue: 1 Volume: 39 Year: 2020 Keywords: optimal power flow; CS algorithm; artificial neural networks; cost minimisation; power loss reduction; synchronous generator. File-URL: http://www.inderscience.com/link.php?id=108833 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:1:p:1-23 Template-Type: ReDIF-Article 1.0 Author-Name: Aida Nazari Gooran Author-X-Name-First: Aida Nazari Author-X-Name-Last: Gooran Author-Name: Hamed Rafiei Author-X-Name-First: Hamed Author-X-Name-Last: Rafiei Author-Name: Masoud Rabbani Author-X-Name-First: Masoud Author-X-Name-Last: Rabbani Title: Evaluation and designing reverse logistics for risk-neutral and risk-seeking decision makers Abstract: Designing appropriate supply chain would provide numerous valuable feedbacks for the whole chain, since using returned products instead of reproducing them, is a more appropriate response to the environmental concerns on the one hand which provides benefit and financial savings for the chains on the other hand. Therefore, this paper presents a three-objective function mathematical model to maximise financial savings and quantities of returned products to the chain and minimise total costs in terms of uncertainty and risk that derives from reverse logistics nature. Finally, the developed model was solved by Monte Carlo simulation and genetic algorithm along with proper risk measures for risk-neutral and risk-seeking decision makers. The results indicated financial savings are one of the best objective functions in order to show superiority of reverse logistics network. As another result, it was pointed out that profitability of the chain increases because of delivering return products before their scrap-life. Journal: Int. J. of Operational Research Pages: 24-49 Issue: 1 Volume: 39 Year: 2020 Keywords: expected value; standard deviation; risk-neutral decision makers; risk-seeking decision makers; reverse logistics; uncertainty; risk; risk measures; genetic algorithms; Monte Carlo simulation. File-URL: http://www.inderscience.com/link.php?id=108834 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:1:p:24-49 Template-Type: ReDIF-Article 1.0 Author-Name: K.V. Geetha Author-X-Name-First: K.V. Author-X-Name-Last: Geetha Author-Name: R. Udayakumar Author-X-Name-First: R. Author-X-Name-Last: Udayakumar Title: Economic ordering policy for deteriorating items with inflation induced time dependent demand under infinite time horizon Abstract: This article deals with an economic order quantity (EOQ) model for deteriorating items in which the demand is considered to be inflation induced time dependent under infinite planning horizon. Here, we have considered two different models, that is, shortages are not permitted in model-1 and shortages are permitted with partial backlogging in model-2. The salvage value associated with the deteriorated units is also considered. The objective of this work is to minimise the total inventory cost and to find the optimal length of replenishment and the optimal order quantity. Numerical examples given illustrate the solution procedure. Comparative study between the two developed models is carried out. The insights obtained from managerial point of view are discussed in detail with the aid of sensitivity analysis with respect to major parameters of the inventory system. Journal: Int. J. of Operational Research Pages: 69-94 Issue: 1 Volume: 39 Year: 2020 Keywords: inventory; deterioration; inflation; salvage value; shortage. File-URL: http://www.inderscience.com/link.php?id=108835 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:1:p:69-94 Template-Type: ReDIF-Article 1.0 Author-Name: Sundaram Elango Author-X-Name-First: Sundaram Author-X-Name-Last: Elango Author-Name: R. Subramanian Author-X-Name-First: R. Author-X-Name-Last: Subramanian Author-Name: Venugopal Manikandan Author-X-Name-First: Venugopal Author-X-Name-Last: Manikandan Author-Name: Krishnan Ramakrishnan Author-X-Name-First: Krishnan Author-X-Name-Last: Ramakrishnan Title: Fuzzy logic-based multi-level shunt active power filter for harmonic reduction Abstract: In this paper, using a three level diode clamped multilevel inverter and DC capacitor, a shunt active power filter (SAPF) is implemented to mitigate the supply current harmonics and compensate reactive power drawn from nonlinear load. The advantage of using three-level inverter paves way to reduced harmonic distortion and switching losses. Fuzzy logic control and unit sine vector control are proposed in this paper for generating reference current for the SAPF. The advantage of fuzzy control is that it is based on a linguistic description and does not require a mathematical model of the system. The implementation of fuzzy logic control (FLC) algorithm is executed using MATLAB fuzzy logic tool box. The proposed pulse width modulation (PWM) method produces the switching signals to the inverter from the sampled reference phase voltage magnitudes as in the case of conventional space vector PWM (SVPWM). The simulation results illustrate that the proposed three-level SAPF with low harmonic content in supply current and in phase with the line voltage. The simulation results are validated with prototype model for demonstrating the effectiveness of the system. Journal: Int. J. of Operational Research Pages: 95-115 Issue: 1 Volume: 39 Year: 2020 Keywords: fuzzy logic; active filters; total harmonic distortion; THD; pulse width modulation; reactive power. File-URL: http://www.inderscience.com/link.php?id=108836 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:1:p:95-115 Template-Type: ReDIF-Article 1.0 Author-Name: Mohamed Abdel-Basset Author-X-Name-First: Mohamed Author-X-Name-Last: Abdel-Basset Author-Name: Asmaa Atef Author-X-Name-First: Asmaa Author-X-Name-Last: Atef Author-Name: Abd El-Nasser H. Zaied Author-X-Name-First: Abd El-Nasser H. Author-X-Name-Last: Zaied Title: Constrained project scheduling problem: a survey of recent investigations Abstract: Scheduling projects are very important topic in project management science. Constrained resources project scheduling problem CRPSP is a problem of the purpose of allocating the available resources to specific tasks or activities for achieving specific objectives or purposes such as minimising the makespan or time of the projects, minimising the execution cost of the project, or any other specific objective or more than one objective at the same time (multi-objectives resource constrained project scheduling problems). This paper introduces a survey for procedure scenarios, techniques, and models that are considered the main context history of CRPSP and multi-mode constrained resource project scheduling problems MMCRPSP. It aims to exhibits, highlights, and update the recent CRPSP surveys. The current state of art for recent researches is evaluated and the potential research directions and orientations are pointed. Also a new framework is proposed for the researchers of interest for this domain of research. Journal: Int. J. of Operational Research Pages: 116-143 Issue: 1 Volume: 39 Year: 2020 Keywords: constrained resources project scheduling problem; multi-mode constrained resource projects; exact methods; heuristic methods; meta-heuristic methods. File-URL: http://www.inderscience.com/link.php?id=108837 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:1:p:116-143 Template-Type: ReDIF-Article 1.0 Author-Name: Tim Gruchmann Author-X-Name-First: Tim Author-X-Name-Last: Gruchmann Author-Name: Marcus Brandenburg Author-X-Name-First: Marcus Author-X-Name-Last: Brandenburg Title: Managing unreliability in automotive supply networks – an extension of the joint economic lot size model Abstract: Within assembly network supply chains, supply disruptions can occur on every supplier-buyer link. Managing this network unreliability can help to reduce schedule instability and increases the overall efficiency of the supply chain accordingly. In this line, a stylised assembly network supply chain model is proposed with two suppliers and a single buyer using the joint economic lot sizing approach. This supply network can be disrupted by a shortage occurring at one of the two suppliers due to random machine breakdowns, which consequently creates dependent requirements variations affecting both the buyer and the entire network. First, the basic joint economic lot sizing model is extended by the said schedule instability. Second, a solution approach is presented concerning the determination of optimal lot sizes, the investment into the reliability of the supply network as well as the determination of safety stocks. Furthermore, the sensitivity of relevant model parameters is investigated by means of a numerical example. Managerial implications are accordingly derived focusing on the reliability of the supply network members and internal incentive structures. Journal: Int. J. of Operational Research Pages: 50-68 Issue: 1 Volume: 39 Year: 2020 Keywords: schedule instability; automotive supply networks; joint economic lot sizing; supply unreliability; safety stocks. File-URL: http://www.inderscience.com/link.php?id=108838 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:1:p:50-68 Template-Type: ReDIF-Article 1.0 Author-Name: Santosh Kumar Yadav Author-X-Name-First: Santosh Kumar Author-X-Name-Last: Yadav Author-Name: Dennis Joseph Author-X-Name-First: Dennis Author-X-Name-Last: Joseph Title: Prioritising critical failure factors for the adoption of ERP system using TOPSIS method Abstract: Enterprise resource planning (ERP) applications are complex and difficult to implement. Even after implementation many ERP projects are not used or adopted by employees. Organisations are struggling to convince and motivate employees to adapt smoothly to them. Several personal, managerial and organisational issues contribute to successful adoption. This research paper attempts to identify potential issues that lead to failures in the adoption of ERP systems in enterprises. Earlier studies have identified different contributing issues to the failure of ERP systems. A questionnaire was developed around these significant influencing issues reported in literature and industry people mostly senior managers having good experience with ERP systems were asked to rate the importance of these factors. TOPSIS method was applied to rank the factors based on their importance in the failure of ERP systems. From the results, it is found that poor top management support and poor quality of testing were the two most important critical failure factors for ERP adoption. While implementing ERP systems, an organisation has to give importance to these failure factors based on this rank to ensure ERP implementation success. Journal: Int. J. of Operational Research Pages: 145-159 Issue: 2 Volume: 39 Year: 2020 Keywords: enterprise systems; enterprise resource planning; ERP; ERP failure factors; ERP adoption; TOPSIS. File-URL: http://www.inderscience.com/link.php?id=109753 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:2:p:145-159 Template-Type: ReDIF-Article 1.0 Author-Name: David A. Wood Author-X-Name-First: David A. Author-X-Name-Last: Wood Title: High-level stochastic project cost and duration planning methodology integrating earned duration, schedule and value, criticality, cruciality and downside risk metrics Abstract: A high-level methodology is described to integrate deterministic and stochastic calculations of project networks with parallel pathways of work items. It provides the systematic integration of earned value, earned schedule and earned duration metrics and derivative to-completion forecasts of project cost and duration with stochastically-derived quantitative measures of criticality, cruciality, uncertainty and downside risk measures at project, work item and budget levels. A project network consisting of up to about 50 high-level project work items (rather than hundreds of activities) is evaluated applying critical path analysis using a matrix template that derives the fraction of the project completed at regular intervals (e.g., 2% to 5%) along a baseline planned project schedule – the work-progress-breakdown diagram. This matrix is evaluated for each deterministic and stochastic case providing the key information to derive a spectrum established and novel earned value metrics, and to quantify uncertainty, down-side risk and criticality at the work-item, pathway and project levels. Journal: Int. J. of Operational Research Pages: 160-204 Issue: 2 Volume: 39 Year: 2020 Keywords: project cost duration simulation; stochastic earned value duration metrics; probabilistic project network critical path; duration performance index; DPI; project versus work-item criticality cruciality; quantified project risk uncertainty; project work-progress-breakdown diagrams. File-URL: http://www.inderscience.com/link.php?id=109754 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:2:p:160-204 Template-Type: ReDIF-Article 1.0 Author-Name: Ramanjan Bhattacharya Author-X-Name-First: Ramanjan Author-X-Name-Last: Bhattacharya Author-Name: Rakesh D. Raut Author-X-Name-First: Rakesh D. Author-X-Name-Last: Raut Author-Name: Bhaskar B. Gardas Author-X-Name-First: Bhaskar B. Author-X-Name-Last: Gardas Author-Name: Sachin S. Kamble Author-X-Name-First: Sachin S. Author-X-Name-Last: Kamble Title: Sustainable partner selection: an integrated AHP-TOPSIS approach Abstract: The selection of an efficient partner for any organisation improves its overall performance. In the present research for the selection of an efficient, sustainable partner 49 selection criteria were identified through the exhaustive literature review, and by applying the Delphi technique, the evaluation criteria was reduced to 16. Later, analytic hierarchy process (AHP) was employed for calculating the relative weights of the short listing criteria. Then, the technique for order preference by similarity to ideal solution (TOPSIS) methodology was used for ranking the partners. The results of the AHP approach revealed that cost (includes environmental cost)/price (C8), environmental competencies (concern for environment) (C15), and human resource management and human rights issues (C9) are the top three significant selection criteria and the results of TOPSIS highlighted that 'partner B' is the best partner amongst the three identified partners. The developed model is intended to guide the decision and policy makers in identifying the significance or importance of selection criteria, and for formulating the strategies or policies for the selection of efficient partners. Journal: Int. J. of Operational Research Pages: 205-236 Issue: 2 Volume: 39 Year: 2020 Keywords: partner selection; multi-criteria decision making; MCDM; Delphi; analytic hierarchy process; AHP; TOPSIS; textile industry. File-URL: http://www.inderscience.com/link.php?id=109755 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:2:p:205-236 Template-Type: ReDIF-Article 1.0 Author-Name: Harun Öztürk Author-X-Name-First: Harun Author-X-Name-Last: Öztürk Title: A deterministic production inventory model with defective items, imperfect rework process and shortages backordered Abstract: The basic assumption of the conventional inventory models is that all items produced are of perfect quality. In practice, some defective items are produced due to process deterioration or other factors. This paper develops a mathematical model for an imperfect production inventory system. It is assumed that the defective items produced in the regular production process consist of scrap, imperfect quality and reworkable items. The rework process is accomplished immediately when the regular production process ends, and the rework process produces scrap, imperfect quality and as-good-as perfect items. A numerical example is provided to illustrate the developed model, and a sensitivity analysis is carried out. It was found that producing scrap and imperfect quality items through the reworking is crucial, since this assumption effects optimal policy. Managerial insights are also presented based on the numerical examples. Journal: Int. J. of Operational Research Pages: 237-261 Issue: 2 Volume: 39 Year: 2020 Keywords: inventory management; production planning; screening; defective items; imperfect rework process; shortages. File-URL: http://www.inderscience.com/link.php?id=109756 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:2:p:237-261 Template-Type: ReDIF-Article 1.0 Author-Name: Chaimongkol Limpianchob Author-X-Name-First: Chaimongkol Author-X-Name-Last: Limpianchob Author-Name: Masahiro Sasabe Author-X-Name-First: Masahiro Author-X-Name-Last: Sasabe Author-Name: Shoji Kasahara Author-X-Name-First: Shoji Author-X-Name-Last: Kasahara Title: A push strategy optimisation model for a marine shrimp farming supply chain network Abstract: Marine shrimp farming operations in Southeast Asia are still traditional and need to be improved in efficiency. In this paper, we first model a marine shrimp supply chain network, which consists of suppliers, farms, distribution centres, traders, and consumers. We also develop a mixed-integer linear programming under the push strategy framework in order to maximise the farmer's profit. Through a sensitivity analysis, we examine how the increase in costs affects the profits. The computational results are presented to demonstrate the feasibility of a real case of smart marine shrimp farming. Journal: Int. J. of Operational Research Pages: 262-277 Issue: 2 Volume: 39 Year: 2020 Keywords: push strategy; supply chain network; SCN; mixed-integer linear programming; MILP; marine shrimp farming; giant freshwater prawns. File-URL: http://www.inderscience.com/link.php?id=109757 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:2:p:262-277 Template-Type: ReDIF-Article 1.0 Author-Name: R.P. Nithya Author-X-Name-First: R.P. Author-X-Name-Last: Nithya Author-Name: M. Haridass Author-X-Name-First: M. Author-X-Name-Last: Haridass Title: Cost optimisation and maximum entropy analysis of a bulk queueing system with breakdown, controlled arrival and multiple vacations Abstract: This article analyses a bulk queueing system with multiple vacations, controlled arrival and breakdown. The service is done in bulk with a minimum of 'a' customers and a maximum of 'b' customers. The server is assigned for secondary jobs (vacations) repeatedly when the number of customers is inadequate to process. The arrivals are accepted with a probability α, β and γ during the busy, vacation and renovation period respectively. During a batch service, if the server breaks down with probability <i>π</i>, the service for the particular batch is processed without interruption. Upon completion of service, the renovation of service station will be considered. The probability generating function for the queue size at an arbitrary time epoch is derived. Various performance measures are obtained. A few particular cases are discussed. Maximum entropy analysis is carried out and validated through numerical illustration. The cost model is also developed to optimise the cost. Journal: Int. J. of Operational Research Pages: 279-305 Issue: 3 Volume: 39 Year: 2020 Keywords: bulk arrival; batch service; multiple vacations; breakdown; controlled arrival; maximum entropy principle; MEP. File-URL: http://www.inderscience.com/link.php?id=110476 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:3:p:279-305 Template-Type: ReDIF-Article 1.0 Author-Name: Arash Apornak Author-X-Name-First: Arash Author-X-Name-Last: Apornak Author-Name: Abbas Keramati Author-X-Name-First: Abbas Author-X-Name-Last: Keramati Title: Pricing and cooperative advertising decisions in a two-echelon dual-channel supply chain Abstract: Developments of e-commerce lead manufacturers and retailers to open direct online channel versus traditional channel in the market. In this paper we consider a supply chain consisting of a manufacturer and a retailer evaluate the impact of price schemes and cooperative advertising mechanisms on dual-channel supply chain competition in traditional and direct online channels as its setting by using Nash equilibrium and cooperative game then find the optima value of each decision variable of the study under preferred scenarios. According to the results the value of decision variables in traditional channel is more than direct online channel in both scenario and also in profit improvement part the analyses shows both channel is sensitive to demand. The results of this study can help managers to consider the interplay between the upstream and downstream entities of a dual-channel. Journal: Int. J. of Operational Research Pages: 306-324 Issue: 3 Volume: 39 Year: 2020 Keywords: pricing; cooperative advertising; Nash equilibrium; cooperative game; two echelon supply chain. File-URL: http://www.inderscience.com/link.php?id=110477 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:3:p:306-324 Template-Type: ReDIF-Article 1.0 Author-Name: Maryam Mohammadi Author-X-Name-First: Maryam Author-X-Name-Last: Mohammadi Author-Name: Siti Nurmaya Musa Author-X-Name-First: Siti Nurmaya Author-X-Name-Last: Musa Author-Name: Mohd Bin Omar Author-X-Name-First: Mohd Bin Author-X-Name-Last: Omar Title: Optimisation of multi-plant capacitated lot-sizing problems in an integrated supply chain network using calibrated metaheuristic algorithms Abstract: In this paper, a mathematical model for a multi-item multi-period capacitated lot-sizing problem in an integrated supply chain network composed of multiple suppliers, plants and distribution centres is developed. The combinations of several functions such as purchasing, production, storage, backordering and transportation are considered. The objective is to simultaneously determine the optimal raw material order quantity, production and inventory levels, and the transportation amount, so that the demand can be satisfied with the lowest possible cost. Transfer decisions between plants are made when demand at a plant can be fulfilled by other production sites to cope with the under-capacity and stock-out problems of that plant. Since the proposed model is NP-hard, a genetic algorithm is used to solve the model. To validate the results, particle swarm optimisation and imperialist competitive algorithm are applied to solve the model as well. The results show that genetic algorithm offers better solution compared to other algorithms. Journal: Int. J. of Operational Research Pages: 325-363 Issue: 3 Volume: 39 Year: 2020 Keywords: capacitated lot-sizing; multi-plant; production and distribution planning; integrated supply chain; optimisation; metaheuristic algorithms; genetic algorithm; GA; particle swarm optimisation; PSO; imperialist competitive algorithm; ICA. File-URL: http://www.inderscience.com/link.php?id=110478 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:3:p:325-363 Template-Type: ReDIF-Article 1.0 Author-Name: Moonyoung Yoon Author-X-Name-First: Moonyoung Author-X-Name-Last: Yoon Author-Name: James Bekker Author-X-Name-First: James Author-X-Name-Last: Bekker Title: Multi-objective simulation optimisation on discrete sets: a literature review Abstract: Simulation optimisation is an interesting and fast-growing research field fostered by advances in computer technology and increased computing power. These advances have made it possible to solve complex stochastic optimisation problems using simulation. Most simulation optimisation studies focus on single-objective simulation optimisation (SOSO), and multi-objective simulation optimisation (MOSO) has only recently drawn attention. This paper provides an overview of recent studies on discrete MOSO problems. We surveyed various MOSO algorithms and classified them, based on: 1) the size of the feasible solution space; 2) the method of dealing with the multiple objectives. For the latter, we identified three categories, namely scalarisation methods, the constraint approach, and the Pareto approach. MOSO algorithms in each category are discussed in some detail. We conclude the paper by discussing some related issues in MOSO, which include noise handling techniques and the issue of exploration versus exploitation. Journal: Int. J. of Operational Research Pages: 364-405 Issue: 3 Volume: 39 Year: 2020 Keywords: simulation; optimisation; multi-objective; ranking; selection. File-URL: http://www.inderscience.com/link.php?id=110482 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:3:p:364-405 Template-Type: ReDIF-Article 1.0 Author-Name: M.D.H. Gamal Author-X-Name-First: M.D.H. Author-X-Name-Last: Gamal Author-Name: Zulkarnain Author-X-Name-First: Author-X-Name-Last: Zulkarnain Author-Name: M. Imran Author-X-Name-First: M. Author-X-Name-Last: Imran Title: Rotary heuristic for uncapacitated continuous location-allocation problems Abstract: This paper proposes a constructive heuristic method to solve location-allocation problems. Specifically, we consider the problem of locating <i>m</i> new facilities in a continuous region such that the sum of the weighted distances from the new facilities to <i>n</i> existing facilities is minimised. The distance is measured using the Euclidean-distance metric. This simple technique shows that the solution found is encouraging for the case where the number of users is much larger than the number of facilities to be located. Journal: Int. J. of Operational Research Pages: 406-415 Issue: 3 Volume: 39 Year: 2020 Keywords: uncapacitated continuous location; location-allocation; constructive heuristic; Euclidean-distance metric. File-URL: http://www.inderscience.com/link.php?id=110483 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:3:p:406-415 Template-Type: ReDIF-Article 1.0 Author-Name: Raveena Suvarna Author-X-Name-First: Raveena Author-X-Name-Last: Suvarna Author-Name: Sunith Hebbar Author-X-Name-First: Sunith Author-X-Name-Last: Hebbar Title: Economic allocation of farm land for commercial crops – a case study in Kasargod Region of India Abstract: Economic allocation of land is an important activity in agricultural planning. Due to the changing prices of crops in market, it's vital for a farmer to appropriately allocate the land for the various crops to maximise the income. Therefore, this study focuses on allocation of land for commercial crops, namely arecanut, pepper, coconut and rubber. Initially, linear programming technique was applied to determine the optimum crop mix. The results of which is then compared with the traditional method adopted by the farmer. A sensitivity analysis was then performed to determine the optimal capital requirement. Later on to predict the behaviour of the income on a long run a SD model was developed. The factors like market price, cost of crops and weather conditions on yield were considered. The simulation results predicted that by 2030, the income will rise by 59% than the current condition if the suggested crop-mix is adopted. Journal: Int. J. of Operational Research Pages: 416-438 Issue: 3 Volume: 39 Year: 2020 Keywords: commercial crops; linear programming model; optimisation of crops; system dynamics; India. File-URL: http://www.inderscience.com/link.php?id=110484 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:3:p:416-438 Template-Type: ReDIF-Article 1.0 Author-Name: Bing-Hai Zhou Author-X-Name-First: Bing-Hai Author-X-Name-Last: Zhou Author-Name: Ke Wang Author-X-Name-First: Ke Author-X-Name-Last: Wang Title: A modified column generation algorithm for scheduling problem of reentrant hybrid flow shops with queue constraints Abstract: This paper investigates a two-stage reentrant hybrid flow shops scheduling problem. In this problem, each product is processed layer by layer with different processing time. To be more practical, the queue time between the parallel machines and the batch processing machine is restricted. The objective is to minimise the total completion time. A column generation algorithm is proposed to solve the scheduling problem by decomposing this problem into main problem and workpiece level sub-problem. In the proposed method, dynamic programming with multiple decision-making is designed to solve each sub-problem and the adaptive accelerating strategy is provided creatively to effectively improve the convergence of the algorithm. In the branch-and-bound method to generate feasible solution, the innovative method of neighbourhood mutation is employed. Computational experiments demonstrate that the proposed method for the two-stage hybrid flow shops problem is quite stable and effective compared with other conventional formulation. Journal: Int. J. of Operational Research Pages: 439-458 Issue: 4 Volume: 39 Year: 2020 Keywords: reentrant hybrid flow shops; queue time; column generation; dynamic programming; branch-and-bound. File-URL: http://www.inderscience.com/link.php?id=111338 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:4:p:439-458 Template-Type: ReDIF-Article 1.0 Author-Name: Ahteshamul Haq Author-X-Name-First: Ahteshamul Author-X-Name-Last: Haq Author-Name: Murshid Kamal Author-X-Name-First: Murshid Author-X-Name-Last: Kamal Author-Name: Srikant Gupta Author-X-Name-First: Srikant Author-X-Name-Last: Gupta Author-Name: Irfan Ali Author-X-Name-First: Irfan Author-X-Name-Last: Ali Title: Multi-objective production planning problem: a case study for optimal production Abstract: In this paper, we have formulated a multi-objective production planning model for a hardware firm. This firm produces different types of hardware locks and other items in their production run. The objectives of the firm are to minimise the production cost, minimise the inventory holding cost and maximise the net profit subject to the set of realistic constraints. The production planning problem of a similar type in the past formulated under the certain environment where the input information precisely known to the decision maker (DM). However, in most of the situations, the input information is not precisely known. In such situations, fuzzy set theory plays a vital role in modelling of the problem where the input data has some vagueness. The proposed model of production planning also been formulated under fuzzy environment. Both triangular and trapezoidal fuzzy numbers used to present the vagueness in the input information. The equivalent crisp form of the fuzzy model obtained by two different defuzzification approaches namely ranking function and α-cut approach. Henceforth, the formulated models under the certain and fuzzy environment have been solved by the fuzzy goal programming approach. Journal: Int. J. of Operational Research Pages: 459-493 Issue: 4 Volume: 39 Year: 2020 Keywords: production planning problem; multi-objective optimisation; fuzzy goal programming; fuzzy set theory. File-URL: http://www.inderscience.com/link.php?id=111339 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:4:p:459-493 Template-Type: ReDIF-Article 1.0 Author-Name: Hasnaa Rezki Author-X-Name-First: Hasnaa Author-X-Name-Last: Rezki Author-Name: Brahim Aghezzaf Author-X-Name-First: Brahim Author-X-Name-Last: Aghezzaf Title: A hybrid GRASP for solving the bi-objective orienteering problem Abstract: This paper focuses on the bi-objective orienteering problem (BOOP) that arises in the tourist routes design problem in cities. In this multi-objective extension of the well-known orienteering problem (OP), each point of interest has different profits, which could reflect the multiple preferences of tourists. The aim is to find routes, limited in travel time, that visit some points of interest and provide the maximum of the different total collected profits. In order to determine an effective approximation of the Pareto optimal solutions, we propose a hybrid greedy randomised adaptive search procedure (GRASP) in which a general variable neighbourhood search (GVNS) is used as an improvement phase. To evaluate the performance of the proposed approach compared to the Pareto variable neighbourhood search (P-VNS) technique, we have used the test instances and the results provided by the P-VNS taken from the literature. Computational results reveal that the hybrid GRASP algorithm generates better approximations of Pareto-optimal solutions compared to the P-VNS method. Journal: Int. J. of Operational Research Pages: 494-515 Issue: 4 Volume: 39 Year: 2020 Keywords: bi-objective orienteering problem; BOOP; greedy randomised adaptive search procedure; GRASP; general variable neighbourhood search; GVNS; hybrid; Pareto-optimal solutions. File-URL: http://www.inderscience.com/link.php?id=111340 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:4:p:494-515 Template-Type: ReDIF-Article 1.0 Author-Name: Cinzia Muriana Author-X-Name-First: Cinzia Author-X-Name-Last: Muriana Title: Inventory management policy for perishable products with Weibull deterioration and constrained recovery assumption based on the residual life Abstract: Economic order quantity models for perishable products generally disregard the relationship between the deterioration rate and the characteristic life (CL). They assume that the cycle time is lower than the CL, and the products that are in stock at the end of the cycle time are considered as outdated. This involves that still fresh products are salvaged at discounted price or disposed of. The paper presents an inventory model for perishable products, namely open dating and fruit and vegetables, in the presence of time-varying CL, Weibull deterioration model and uncertain demand. The relationship between the Weibull deterioration model and the CL is enforced, determining whether to dispose of the products or salvage them at alternative markets. Results show that the model can be solved and the operating variables optimised. Journal: Int. J. of Operational Research Pages: 516-538 Issue: 4 Volume: 39 Year: 2020 Keywords: EOQ model; characteristic life; Weibull deterioration; open dating foods; fruit and vegetables; mean residual life; MRL; perishable products; inventory management. File-URL: http://www.inderscience.com/link.php?id=111341 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:4:p:516-538 Template-Type: ReDIF-Article 1.0 Author-Name: Zachary E. Bowden Author-X-Name-First: Zachary E. Author-X-Name-Last: Bowden Author-Name: Cliff T. Ragsdale Author-X-Name-First: Cliff T. Author-X-Name-Last: Ragsdale Title: The general pickup and delivery problem with backtracking restrictions Abstract: This paper introduces a model for the general pickup and delivery problem (GPDP) that provides a novel approach to limit the amount of backtracking allowed in the solution. This problem is motivated by the increase in peer-to-peer vehicle transactions via online marketplaces such as eBay and an associated increase in the direct consumer procurement of shipping services for transporting recently purchased vehicles. We approach this problem in the context of a profit seeking objective while considering the cognitive processes and behavioural preferences of the driver as important to the ultimate solution of the routing problem. We offer a method for producing a set of good solutions that are differentiated based on backtracking characteristics of the directional flow of the route. Journal: Int. J. of Operational Research Pages: 539-561 Issue: 4 Volume: 39 Year: 2020 Keywords: vehicle routing; backtracking; PDP; behavioural logistics; profit maximisation. File-URL: http://www.inderscience.com/link.php?id=111342 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:4:p:539-561 Template-Type: ReDIF-Article 1.0 Author-Name: Barbara König Author-X-Name-First: Barbara Author-X-Name-Last: König Author-Name: Rainer Leisten Author-X-Name-First: Rainer Author-X-Name-Last: Leisten Author-Name: Jan Stückrath Author-X-Name-First: Jan Author-X-Name-Last: Stückrath Title: Permutation flow shop scheduling: variability of completion time differences – NP-completeness Abstract: We consider the permutation flow shop scheduling problem and aim to obtain smoothness of jobs' completion times, by minimising the variance or the variability of inter-completion times. This problem, including an efficient heuristics, was introduced in Leisten and Rajendran (2015). Here we solve an open problem from that paper and show that the problem for more than two machines is NP-complete. Journal: Int. J. of Operational Research Pages: 562-573 Issue: 4 Volume: 39 Year: 2020 Keywords: flow shop scheduling; variability of completion time differences; NP-completeness; optimisation; operational research. File-URL: http://www.inderscience.com/link.php?id=111343 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:39:y:2020:i:4:p:562-573