Template-Type: ReDIF-Article 1.0 Author-Name: Kasun Bandara Author-X-Name-First: Kasun Author-X-Name-Last: Bandara Author-Name: Rob J. Hyndman Author-X-Name-First: Rob J. Author-X-Name-Last: Hyndman Author-Name: Christoph Bergmeir Author-X-Name-First: Christoph Author-X-Name-Last: Bergmeir Title: MSTL: a seasonal-trend decomposition algorithm for time series with multiple seasonal patterns Abstract: The decomposition of time series into components is an important task that helps to understand time series and can enable better forecasting. Nowadays, with high sampling rates leading to high-frequency data (such as daily, hourly, or minutely data), many datasets contain time series data that can exhibit multiple seasonal patterns. Although several methods have been proposed to decompose time series better under these circumstances, they are often computationally inefficient or inaccurate. We propose a procedure to decompose time series with multiple seasonal patterns that is suited to a wide range of high-frequency data. The procedure for multiple seasonal trend decomposition (MSTL) introduced in this paper extends the traditional seasonal-trend decomposition using Loess (STL) algorithm, allowing the decomposition of time series with multiple seasonal patterns. In our evaluation on synthetic and a perturbed real-world time series dataset, compared to other decomposition benchmarks, MSTL demonstrates competitive results with lower computational cost. The implementation of MSTL is available in the R package <i>forecast</i>. Journal: Int. J. of Operational Research Pages: 79-98 Issue: 1 Volume: 52 Year: 2025 Keywords: time series decomposition; multiple seasonality; MSTL; TBATS; STR. File-URL: http://www.inderscience.com/link.php?id=143957 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:1:p:79-98 Template-Type: ReDIF-Article 1.0 Author-Name: G. Ayyappan Author-X-Name-First: G. Author-X-Name-Last: Ayyappan Author-Name: K. Thilagavathy Author-X-Name-First: K. Author-X-Name-Last: Thilagavathy Title: Analysis of (MAP, PH)/(PH, PH)/1 retrial queueing model with standby server, collision of orbital customers, breakdowns, two-way communication, phase type repairs, constant retrial rate and impatient behaviour of customers Abstract: Our system was modelled using standby server (SS) whenever a main server (MS) is unavailable due to breakdowns and analysed the constant retrial policy as well as collision for the orbital customers. The incoming arrival (IA) of customers follows the Markovian arrival process (MAP). The outgoing arrival (OA) of customers, service for both incoming and outgoing arrival of customers, and repairs are all based on the phase-type (PH) distributions. Using matrix analytic method, we investigate the steady state probability vector of the system. We described the busy period as well as cost analysis of the system and some performance of the system measures. Then, we examine some of the numerical as well as graphical representations for this model. Journal: Int. J. of Operational Research Pages: 1-50 Issue: 1 Volume: 52 Year: 2025 Keywords: PH distribution; constant retrial rate; Markovian arrival process; MAP; two-way communication; standby server; impatient behaviour. File-URL: http://www.inderscience.com/link.php?id=143958 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:1:p:1-50 Template-Type: ReDIF-Article 1.0 Author-Name: Nejmaddin A. Sulaiman Author-X-Name-First: Nejmaddin A. Author-X-Name-Last: Sulaiman Author-Name: Gulnar W. Sadiq Author-X-Name-First: Gulnar W. Author-X-Name-Last: Sadiq Author-Name: Basiya K. Abdulrahim Author-X-Name-First: Basiya K. Author-X-Name-Last: Abdulrahim Title: A novel technique for solving bi-level linear fractional programming problems with fuzzy interval coefficients Abstract: In this paper, a bi-level linear fractional programming problem (BILLFPP) with fuzzy interval coefficient (FIC) is contemplated, where all of it is coefficients in the goal function and constraints are fuzzy intervals (FIs). Firstly, to resolve this issue, we are going to construct two LFPP with fuzzy coefficients. Before all else, of these issues is a LFPP where all of coefficients are upper approximations of FIs and the other is a LFPP where all of coefficients are lower approximations of FIs. Secondly, the BILLFPP is transformed to the form of single goal LFPP and QFPP. We address problems with a factorised or non-factorised optimisation problem and homogeneous or non-homogeneous constraints. Our proposed technique is based on a mathematical model that converts the QFPP to a LPP by solving the problem in an algebraic expression with a Taylor series. This technique, which is based on the LPP solution, can be applied to specific problems. NLFPP containing nonlinear constraints, on iterative processes, it decreases the overall processing time. Further explanations of the novel technique for solving BILLFPP are made by taking numerical examples and comparing with Jayalakshmi (2015) and Syaripuddin et al. (2017). Journal: Int. J. of Operational Research Pages: 99-115 Issue: 1 Volume: 52 Year: 2025 Keywords: LFPP; bi-level linear fractional programming problem; BILLFPP; FBILLFPP; BILLFPP with fuzzy interval; FBILLFPP with FIC; QFPP; Taylor series; a novel technique; fuzzy interval coefficient; FIC. File-URL: http://www.inderscience.com/link.php?id=143959 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:1:p:99-115 Template-Type: ReDIF-Article 1.0 Author-Name: Vikas Singla Author-X-Name-First: Vikas Author-X-Name-Last: Singla Title: An integrated systematic layout planning, analytical hierarchy process and nonlinear programming approach to facility layout design Abstract: This study has three aims: 1) finding alternative layout designs through procedural approach of SLP of a large-scale auto component manufacturer; 2) examine optimality of identified alternatives by using both qualitative and quantitative criteria and ranking them by using AHP method by collecting data from decision-makers of similar 132 manufacturers; 3) identifying most optimal design by using mathematical optimisation model of NLP. Results of SLP provided three prominent quantitative criteria by comparing key performance indicators of four alternative designs with those of existing layout. Informal discussions extracted major qualitative criteria. Rating of all six criteria indicated distance and cost of change being primary influencers. Results of NLP were able to identify one most optimal alternative from feasible four derived from SLP. The study derives its originality by dealing with shortcoming of SLP approach of over emphasis on subjective criteria and of metaheuristic methods of assigning excessive importance to metaheuristic methods. Journal: Int. J. of Operational Research Pages: 128-145 Issue: 1 Volume: 52 Year: 2025 Keywords: facility layout; systematic layout planning; SLP; analytic hierarchy process; AHP; nonlinear programming; NLP; quadratic assignment problem; QAP. File-URL: http://www.inderscience.com/link.php?id=143960 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:1:p:128-145 Template-Type: ReDIF-Article 1.0 Author-Name: R. Narmada Devi Author-X-Name-First: R. Narmada Author-X-Name-Last: Devi Author-Name: S. Sowmiya Author-X-Name-First: S. Author-X-Name-Last: Sowmiya Title: On solving game problem using octagonal neutrosophic fuzzy number Abstract: Game theory deals with competitive situations where there are two or more opposing parties with conflicting interests are involved. A competitive situation will be called a game. In this paper, a new approach for selecting the best strategy for increasing the shares for two companies using octagonal neutrosophic fuzzy numbers is proposed. Further, an octagonal neutrosophic fuzzy number to neutrosophic fuzzy number is converted by using deneutrosophication the fuzzy number is obtained by using the fuzzification method. The obtained matrix represents a fuzzy game matrix. This matrix is solved using game theory to obtain the best strategy for these companies. Journal: Int. J. of Operational Research Pages: 116-127 Issue: 1 Volume: 52 Year: 2025 Keywords: octagonal neutrosophic fuzzy number; ONFN; DTNON: de-neutrosophication of trueness; DINON: de-neutrosophication of indeterminacy; DFNON: de-neutrosophication of falsity. File-URL: http://www.inderscience.com/link.php?id=143961 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:1:p:116-127 Template-Type: ReDIF-Article 1.0 Author-Name: Sundar Lal Author-X-Name-First: Sundar Author-X-Name-Last: Lal Author-Name: Ashok Kumar Author-X-Name-First: Ashok Author-X-Name-Last: Kumar Author-Name: Sandeep Kumar Author-X-Name-First: Sandeep Author-X-Name-Last: Kumar Title: Development of two-shop inventory model with multi-variate demand and screening errors under controllable carbon emission Abstract: This study proposes an inventory model for the retailer by considering two shops under single management. This study considers that: 1) receive lot contains defective items; 2) manual screening process is carried out which is an erroneous process; 3) demand is multi-variate; 4) carbon emissions due to operational activities linked to inventory which is regulated by cap-and-tax policy; 5) capital investment in green technology to curb carbon emission. The present study aims to determine the values of order quantity and backorder level that optimise the retailer's profit. Developed model is illustrated with the help of numerical analysis as well as sensitivity analysis. In the end, the effect of promotion activities, selling price, cap-and-tax regulation policy, and investment in green technology on the optimal decision have been analysed. Based on the analysis, managerial implications are also presented. Journal: Int. J. of Operational Research Pages: 51-78 Issue: 1 Volume: 52 Year: 2025 Keywords: EOQ; imperfect lot; screening error; cap-and-tax regulation; carbon emissions; multi-variate demand; two-shop management. File-URL: http://www.inderscience.com/link.php?id=143976 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:1:p:51-78 Template-Type: ReDIF-Article 1.0 Author-Name: Marcelo Carneiro Gonçalves Author-X-Name-First: Marcelo Carneiro Author-X-Name-Last: Gonçalves Author-Name: Rafael Rodrigues Guimarães Wollmann Author-X-Name-First: Rafael Rodrigues Guimarães Author-X-Name-Last: Wollmann Author-Name: Raimundo José Borges De Sampaio Author-X-Name-First: Raimundo José Borges De Author-X-Name-Last: Sampaio Title: Proposal of a numerical approximation theory to solve the robust convex problem of production planning Abstract: This research seeks to solve the production planning problem modelled as a queuing system to propose to managers a production planning model that uses efficient, simple and robust methods. First, a robust mathematical model of nonlinear programming was proposed considering the concepts of queuing systems to estimate production capacity. Next, this model was approximated by a family of affine functions using the strategy of approximating a convex set by a polyhedral set. Finally, a theorem was proposed to demonstrate that a robust nonlinear programming model can be approximated by a robust linear programming model. From a numerical experiment with data from an electronic equipment company, it was possible to observe the effectiveness of the approximation method. Journal: Int. J. of Operational Research Pages: 171-191 Issue: 2 Volume: 52 Year: 2025 Keywords: robust optimisation; linear programming; convex programming; queuing systems. File-URL: http://www.inderscience.com/link.php?id=144318 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:2:p:171-191 Template-Type: ReDIF-Article 1.0 Author-Name: Prasham Sheth Author-X-Name-First: Prasham Author-X-Name-Last: Sheth Author-Name: Praxal Patel Author-X-Name-First: Praxal Author-X-Name-Last: Patel Author-Name: Priyank Thakkar Author-X-Name-First: Priyank Author-X-Name-Last: Thakkar Title: Optimal location prediction for emergency stations using machine learning Abstract: Time is a critical aspect in emergency circumstances like medical crises, natural disasters, breaking out of a fire, etc. The average response time of emergency services is on the rise in recent times owing to the growing traffic. This has raised some serious concerns for people's safety. It is easy to perceive that optimally located emergency stations (e.g., ambulance, fire station) can help in these situations by minimising travel time to reach the location of casualty. With this motivation, we propose an approach which employs K-medoids driven by extreme gradient boosting (XGBoost) for predicting optimal locations of emergency stations. The proposed approach is validated on real datasets, namely: New York City, USA 100-metre Grid Coordinates, NYC Taxi Trip Duration, KNYC Metars 2016 and FDNY Firehouse Listing dataset and the results demonstrate that the proposed method reduces normal average response time and allows serving more locations. Journal: Int. J. of Operational Research Pages: 230-251 Issue: 2 Volume: 52 Year: 2025 Keywords: emergency station; optimal location prediction; OLP; machine learning; XGBoost; K-medoids; average response time. File-URL: http://www.inderscience.com/link.php?id=144319 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:2:p:230-251 Template-Type: ReDIF-Article 1.0 Author-Name: Prokash Mondal Author-X-Name-First: Prokash Author-X-Name-Last: Mondal Author-Name: Asim Kumar Das Author-X-Name-First: Asim Kumar Author-X-Name-Last: Das Author-Name: Tapan Kumar Roy Author-X-Name-First: Tapan Kumar Author-X-Name-Last: Roy Author-Name: Surajit Naskar Author-X-Name-First: Surajit Author-X-Name-Last: Naskar Title: An EOQ model for deteriorating item with ramp type linear time dependent demand and time dependent partial backorder Abstract: In this present article we have developed an economic order quantity (EOQ) model over a finite time horizon for an item with a liner time dependent demand rate with constant rate of deterioration in consideration of shortages (SFI policy) in inventory under permissible delay in payments and partial backlogging. Studied witnessed that the demand always play a pivot role in the inventory model, due to COVID crisis there is a shift in the paradigm on the demand characteristics. This model studied the shifting demand rate after stock out period. Mathematical models are also developed under two distinct circumstances, i.e., case 1: the trade credit is before the stock out period and case 2: the trade credit scheduled after stock out period. The results are illustrated with numerically and graphically. The sensitivity analysis of key parameters of the optimal solution has also been conducted to study the effect of the parameter. Journal: Int. J. of Operational Research Pages: 147-170 Issue: 2 Volume: 52 Year: 2025 Keywords: inventory; economic order quantity; EOQ; deterioration; delay in payment; trade credit; backlog dependent. File-URL: http://www.inderscience.com/link.php?id=144320 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:2:p:147-170 Template-Type: ReDIF-Article 1.0 Author-Name: Yaguang Yang Author-X-Name-First: Yaguang Author-X-Name-Last: Yang Author-Name: Fabio Vitor Author-X-Name-First: Fabio Author-X-Name-Last: Vitor Title: A double-pivot degenerate-robust simplex algorithm for linear programming Abstract: A double pivot simplex algorithm that combines features of two recently published papers by these authors is proposed. The proposed algorithm is implemented in MATLAB. The MATLAB implementation is tested, along with a MATLAB implemention of Dantzig's algorithm, for several test sets, including a set of cycling linear programming problems, Klee-Minty's problems, randomly generated linear programs, and Netlib benchmark problems. The test results show that the proposed algorithm, with a careful implementation is: 1) degenerate-robust as expected; 2) more efficient than Dantzig's algorithm for large size randomly generated linear programming problems, but less efficient for Netlib benchmark problems and small size randomly generated problems in terms of CPU time. Journal: Int. J. of Operational Research Pages: 192-210 Issue: 2 Volume: 52 Year: 2025 Keywords: double pivots; degenerate-robust; simplex method; linear programming; Klee-Minty cube. File-URL: http://www.inderscience.com/link.php?id=144321 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:2:p:192-210 Template-Type: ReDIF-Article 1.0 Author-Name: Vadim V. Romanuke Author-X-Name-First: Vadim V. Author-X-Name-Last: Romanuke Title: General finite approximation of non-cooperative games played in staircase-function continuous spaces Abstract: A method of general finite approximation of <i>N</i>-person games played with staircase-function strategies is presented. A continuous staircase <i>N</i>-person game is approximated to a staircase <i>N</i>-dimensional-matrix game by sampling the player's pure strategy value set. The method consists in irregularly sampling the player's pure strategy value set, finding the best equilibria in 'short' <i>N</i>-dimensional-matrix games, each defined on a subinterval where the pure strategy value is constant, and stacking the equilibrium situations if they are consistent. As opposed to straightforwardly solving the sampled staircase game, which is intractable, stacking the subinterval equilibria extremely reduces the computation time. The stack of the 'short' (subinterval) <i>N</i>-dimensional-matrix game equilibria is an approximate equilibrium in the initial staircase game. The (weak) consistency of the approximate equilibrium is studied by how much the payoff and equilibrium situation change as the sampling density minimally increases. The consistency is decomposed into the payoff, equilibrium strategy support cardinality, equilibrium strategy sampling density, and support probability consistency. It is practically reasonable to consider a relaxed payoff consistency. An example of a 4-person staircase game is presented to show how the approximation is fulfilled for a case of when every subinterval 4-dimensional-matrix (quadmatrix) game has pure strategy equilibria. Journal: Int. J. of Operational Research Pages: 252-297 Issue: 2 Volume: 52 Year: 2025 Keywords: game theory; payoff functional; staircase-function strategy; multidimensional-matrix game; approximate equilibrium consistency; equilibrium stacking. File-URL: http://www.inderscience.com/link.php?id=144322 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:2:p:252-297 Template-Type: ReDIF-Article 1.0 Author-Name: S. Kadyan Author-X-Name-First: S. Author-X-Name-Last: Kadyan Author-Name: S.C. Malik Author-X-Name-First: S.C. Author-X-Name-Last: Malik Title: Stochastic analysis of a non-identical repairable system with (n + 1) units subject to MRT of type-I unit Abstract: Here, a repairable system of (<i>n</i> + 1) non-identical units is analysed stochastically by classifying the units as type-I and type-II units subject to maximum repair time (MRT) of type-I unit. In the system, there is one type-I unit and '<i>n</i>' type-II units in cold standby. Type-I unit has been considered as more efficient than type-II units and hence priority for repair and operation is given to it. Type-II units become operative simultaneously on the failure of type-I unit. A single server handles repair and replacement activities of both types of units. If type-I unit is not repaired in a pre-specified time then it undergoes for replacement. Some significant reliability measures including MTSF, availability, expected number of visits and busy period analysis of the server have been obtained. The effect of number of type-II units on these measures is studied. Performance of the developed system is compared with a system without MRT. An application of this work can be envisioned in the power supply system where the transformer is subject to MRT. Journal: Int. J. of Operational Research Pages: 211-229 Issue: 2 Volume: 52 Year: 2025 Keywords: stochastic analysis; repairable system; non-identical units; maximum repair time; MRT; simultaneously working units; reliability. File-URL: http://www.inderscience.com/link.php?id=144338 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:2:p:211-229 Template-Type: ReDIF-Article 1.0 Author-Name: Matthew West Joseph Zilvar Author-X-Name-First: Matthew West Joseph Author-X-Name-Last: Zilvar Title: Linearisation of nonlinear programs using the essence of calculus and integer programming Abstract: This paper contains an approach to solve nonlinear programming (NLP) problems using a linearisation approach based on theorems of calculus. The solution method relies upon dividing functions with finite domains into a series of domains and coefficients used to model linear and nonlinear functions within a mixed integer linear program (MILP). Nonlinear terms are solved for in the objective function and constraints while achieving global optimality at a specified resolution using the international system of units (SI). An efficient solution method is provided by creating a set of MILPs that represent the same problem with different complexities and using the solutions to achieve global optimality. Numerical results and a comparison are provided. From the results an argument in the <i>P</i> versus <i>NP</i> problem is formed. Journal: Int. J. of Operational Research Pages: 334-359 Issue: 3 Volume: 52 Year: 2025 Keywords: linearisation; nonlinear programming; integer programming; P vs. NP; calculus; logarithmic programming; transportation problem; set forming; complexity theory; global optimality; mixed integer linear program; MILP. File-URL: http://www.inderscience.com/link.php?id=144671 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:3:p:334-359 Template-Type: ReDIF-Article 1.0 Author-Name: Sirine Boujelben Author-X-Name-First: Sirine Author-X-Name-Last: Boujelben Author-Name: Mohamed Souissi Author-X-Name-First: Mohamed Author-X-Name-Last: Souissi Title: Comparison of a novel single reference point multi-attribute decision making method with EDAS method Abstract: The present work aims to introduce a new method called the evaluation based on deviation from median attribute values (EDMAV) to solve the multi-attribute decision problems. This method is based on the deviation of each alternative from to the reference median solution with respect to each criterion. However, the proposed method combines the results of two different models to get the global score of each alternative, namely weighted arithmetic mean (WAM) and weighted median model (WMed). A ranking of alternatives is performed based on the value of a joint generalised criteria computed according to the results of these models. The proposed method is applied on illustrative example in order to illustrate its applicability, usefulness, and effectiveness and it has been compared with the evaluation based on distance from average solution (EDAS) method. Journal: Int. J. of Operational Research Pages: 360-381 Issue: 3 Volume: 52 Year: 2025 Keywords: multi-attribute decision; operational research; weighted median; average; single reference point. File-URL: http://www.inderscience.com/link.php?id=144672 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:3:p:360-381 Template-Type: ReDIF-Article 1.0 Author-Name: Sanjeev Kumar Author-X-Name-First: Sanjeev Author-X-Name-Last: Kumar Author-Name: Ashirbad Sarangi Author-X-Name-First: Ashirbad Author-X-Name-Last: Sarangi Author-Name: Rakesh P. Badoni Author-X-Name-First: Rakesh P. Author-X-Name-Last: Badoni Author-Name: R.P. Mohanty Author-X-Name-First: R.P. Author-X-Name-Last: Mohanty Title: Development and validation of a hybridised algorithm involving AHP and machine learning for automobile vehicle selection Abstract: The problem of selecting an automobile has always been one of the most complex decisions to make, given a person's social and economic life. It is often resolved either through a qualitative judgement of vehicles or through multiple criteria decision-making (MCDM) methods in an algorithmic way. However, the modern machine learning (ML) procedures have surfaced themselves as efficient techniques in the field of recommendation engines (REs) to predict the items that may be useful to the customers according to their preferences. In this paper, an attempt has been made to study the automobile vehicle selection (AVS) problem in an innovative manner by hybridising the analytic hierarchical process (AHP) with the collaborative filtering (CF) technique to construct a selector to recommend the customers precisely one pair of cars that would suit best to their preference. The proposed algorithm provides an efficient way to map the satisfaction level of the customers by eliminating the vagueness and complexity in the selection process. We have validated the algorithm using real-life datasets collected by administering an exploratory survey across geographies, including India. Journal: Int. J. of Operational Research Pages: 299-333 Issue: 3 Volume: 52 Year: 2025 Keywords: multiple criteria decision-making; MCDM; analytic hierarchical process; AHP; automobile vehicle selection; AVS; collaborative filtering; CF; recommendation engine; RE; machine learning; ML. File-URL: http://www.inderscience.com/link.php?id=144673 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:3:p:299-333 Template-Type: ReDIF-Article 1.0 Author-Name: S. Jeyakumar Author-X-Name-First: S. Author-X-Name-Last: Jeyakumar Author-Name: B. Logapriya Author-X-Name-First: B. Author-X-Name-Last: Logapriya Title: Modelling MX/G/1 queuing system with optional second service under disaster and repairs with multiple adapted vacation policy Abstract: In this article, the queuing system with disaster is considered in which every customer will receive the essential service and demanded customer alone will receive second optional service. When the system is affected by any of the disaster, the server initiates the repair period and operates under multiple adapted vacation (MAV) policy causing all waiting and served customer to leave the system. Using supplementary variable technique, we procure the queue size distribution with few measures of performance. Expected queue length, expected waiting times and certain special cases are discussed. In addition, the effect of parameters is studied with a numerical illustration. Journal: Int. J. of Operational Research Pages: 382-400 Issue: 3 Volume: 52 Year: 2025 Keywords: supplementary variable technique; second optional service; disaster; multiple adapted vacation policy. File-URL: http://www.inderscience.com/link.php?id=144677 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:3:p:382-400 Template-Type: ReDIF-Article 1.0 Author-Name: Fadwa Bouhannana Author-X-Name-First: Fadwa Author-X-Name-Last: Bouhannana Author-Name: Akram El Korchi Author-X-Name-First: Akram El Author-X-Name-Last: Korchi Title: A systematic literature review to measure lean, green and agile in manufacturing organisations Abstract: Most manufacturing companies are mainly interested in strengthening competiveness by concentrating on competitive priorities. The majority of companies have started implementing lean, green and agile paradigms in order to become more efficient and highly productive. To achieve those objectives, researchers around the world have been increasingly interested in developing tools to control the process of implementing these three paradigms in organisations. In this context, various approaches have previously been proposed in the literature. Consequently, a systematic review of measurement methods, such as leanness, greenness and agility, in manufacturing organisations was performed for the purpose of defining some guidance for managers and practitioners who are interested in measuring these three concepts. Therefore, 121 methods have been selected and analysed based on a set of comparative dimensions. The main strengths and weaknesses of the selected approaches are mentioned. Some literature gaps are highlighted, and a number of directions are provided for future research. Journal: Int. J. of Operational Research Pages: 401-430 Issue: 3 Volume: 52 Year: 2025 Keywords: manufacturing; leanness; greenness; agility; literature review; score. File-URL: http://www.inderscience.com/link.php?id=144679 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:3:p:401-430 Template-Type: ReDIF-Article 1.0 Author-Name: Jayanti Nath Author-X-Name-First: Jayanti Author-X-Name-Last: Nath Author-Name: Sanjoy Chhatri Author-X-Name-First: Sanjoy Author-X-Name-Last: Chhatri Author-Name: Debasish Bhattacharya Author-X-Name-First: Debasish Author-X-Name-Last: Bhattacharya Title: A multi-objective portfolio selection problem with parameters as interval type fuzzy set Abstract: A multi-objective portfolio selection problem with fuzzy parameters is studied here based on the possibility concept of fuzzy set theory. Here, for a given degree of membership <i>α</i> of the fuzzy parameters, the problem has been reduced to an equivalent crisp problem. This reduced problem is then solved by the min-max goal programming (GP) method in one step. This approach gives the decision maker the flexibility to choose the solution of the problem for an assigned degree of satisfaction <i>α</i> and concomitant risk (1 - <i>α</i>), 0 ≤ <i>α</i> ≤ 1. Also, the investor can fix his/her priority among the objectives and compare the solutions for different values of <i>α</i>. The method of solution of the problem has been illustrated by constructing a portfolio selection problem based on real data collected from Bombay Stock Exchange (BSE), National Stock Exchange (NSE), http://www.moneycontrol.com, http://finance.yahoo.com, and http://screener.in, India. Journal: Int. J. of Operational Research Pages: 455-489 Issue: 4 Volume: 52 Year: 2025 Keywords: portfolio optimisation; fuzzy multi-objective linear programming; capital growth; return; risk; liquidity; dividend; min-max GP. File-URL: http://www.inderscience.com/link.php?id=145236 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:4:p:455-489 Template-Type: ReDIF-Article 1.0 Author-Name: Masashi Miyagawa Author-X-Name-First: Masashi Author-X-Name-Last: Miyagawa Author-Name: Takuro Matsumoto Author-X-Name-First: Takuro Author-X-Name-Last: Matsumoto Author-Name: Atsushi Inoue Author-X-Name-First: Atsushi Author-X-Name-Last: Inoue Author-Name: Tatsuo Oyama Author-X-Name-First: Tatsuo Author-X-Name-Last: Oyama Title: Applying mathematical modelling to the factor analyses of obtaining GASR funds for universities in Japan Abstract: First, we briefly explain the historical trend of the Japanese competitive research funding system, focusing on the grants-in-aid for scientific research (GASR). We provide mathematical models, such as logistic curves and Zipf's model, to explain the trend of budgets for research promotion funds and their allocation to Japanese universities and research institutions. Subsequently, we evaluate the performance of Japanese universities from the perspective of obtaining GASR funds using Gini coefficients. We then build multiple regression models to quantitatively investigate the factors that determine and affect the dependent variables, such as the number of accepted GASR projects and number of distributed funds of the GASF projects, in which independent variables including the number of undergraduate students, external funds, operating expenses grants, and operating expenses grants to all university-specific project expenses, or the ratio of external funds per faculty member, may also be considered as influential factors. We apply multivariate analysis techniques such as cluster analysis and principal component analysis to determine the key factors for obtaining GASR, to classify Japanese universities with respect to their recent scenario for obtaining GASR funds and reveal the determining factors underlying these results. Journal: Int. J. of Operational Research Pages: 502-530 Issue: 4 Volume: 52 Year: 2025 Keywords: competitive research fund; scientific research fund; mathematical model; logistic curve; Zipf's model; multiple regression model; cluster analysis; principal component analysis; grants-in-aid for scientific research; GASR; Japan. File-URL: http://www.inderscience.com/link.php?id=145237 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:4:p:502-530 Template-Type: ReDIF-Article 1.0 Author-Name: Sanat Rout Author-X-Name-First: Sanat Author-X-Name-Last: Rout Author-Name: Sadananda Sahoo Author-X-Name-First: Sadananda Author-X-Name-Last: Sahoo Author-Name: Rabindra Kumar Mishra Author-X-Name-First: Rabindra Kumar Author-X-Name-Last: Mishra Title: Priority study on commodity market operation and performance for Indian investors Abstract: The present research explores the investors' behavioural intention towards the commodity market in an emerging economy. Drawing cues from the extant literature, this research identifies and empirically prioritises the dimensions of investor intention regarding commodity trading. Based on the RIDIT analysis, the findings indicate that a lower degree of risk, geopolitical changes, and a higher rate of return are the most important dimensions based on the respondent perceptions. These findings offer newer insights on this under-explored domain to facilitate conceptual development and policy formulation. The portfolio managers, market regulators, and financial institutions can take cues from the study findings to redesign their strategies for attracting investors to commodity exchanges. Journal: Int. J. of Operational Research Pages: 490-501 Issue: 4 Volume: 52 Year: 2025 Keywords: commodities; investor; behavioural intention; emerging economy; RIDIT. File-URL: http://www.inderscience.com/link.php?id=145238 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:4:p:490-501 Template-Type: ReDIF-Article 1.0 Author-Name: G.K. Tamrakar Author-X-Name-First: G.K. Author-X-Name-Last: Tamrakar Author-Name: A. Banerjee Author-X-Name-First: A. Author-X-Name-Last: Banerjee Title: On state dependent batch service queue with single and multiple vacation under Markovian arrival process Abstract: An infinite buffer batch service vacation queue has been studied where service rate of the batch is dependent on the size of the batch and vacation rate is dependent on the queue size at vacation initiation epoch. The arrivals follow the Markovian arrival process (MAP). For service rule, general bulk service (GBS) rule is considered. The service time and vacation time both are considered to be generally distributed. Several joint distributions of interest are obtained using the bivariate vector generating function method and the supplementary variable technique (SVT). Numerical results are presented to show the behaviour of the system performance to validate the analytical results. Journal: Int. J. of Operational Research Pages: 531-557 Issue: 4 Volume: 52 Year: 2025 Keywords: Markovian arrival process; infinite buffer; GBS rule; bivariate VGF; supplementary variable technique. File-URL: http://www.inderscience.com/link.php?id=145239 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:4:p:531-557 Template-Type: ReDIF-Article 1.0 Author-Name: Mostafa Ashour Author-X-Name-First: Mostafa Author-X-Name-Last: Ashour Author-Name: Raafat Elshaer Author-X-Name-First: Raafat Author-X-Name-Last: Elshaer Title: Multi-echelon reverse supply chain network design using new ant colony optimisation algorithms Abstract: Reverse logistics (RL) is becoming more important in the general area of the industry due to environmental and business factors. Planning and implementing a suitable RL network can lead to more benefits, customer satisfaction, and a nice social image for businesses. Since such network design challenges belong to the NP-hard problem class, three proposed ant colony algorithms that differ in the heuristic information, and artificial pheromone trail calculation rules were developed to solve a designed distribution-allocation problem in multi-stage RL network with a fixed transportation cost in distribution network as well as variable cost of the route. Five network characteristics with different sizes are designed, and thirty instances are randomly generated for each network characteristic to evaluate the performance of the three developed ant colony optimisation (ACO) algorithms. Computational analysis of the results reveals the high quality and validity of the developed ACO algorithms when compared with the exact results. Journal: Int. J. of Operational Research Pages: 431-454 Issue: 4 Volume: 52 Year: 2025 Keywords: logistics network; forward/reverse supply chain; single-objective; ant colony optimisation; ACO. File-URL: http://www.inderscience.com/link.php?id=145240 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:4:p:431-454 Template-Type: ReDIF-Article 1.0 Author-Name: S. Paulraj Author-X-Name-First: S. Author-X-Name-Last: Paulraj Author-Name: G. Tamilarasi Author-X-Name-First: G. Author-X-Name-Last: Tamilarasi Title: A LINMAP approach for determining subjective attribute weights for neutrosophic multi-attribute decision-making models Abstract: The linear programming technique for multidimensional analysis of preference (LINMAP) is one of the well-known methods involved to solve multi-attribute decision-making (MADM) problems. Many authors developed LINMAP method based on fuzzy and intuitionistic fuzzy environment. In this paper, we develop a new method called neutrosophic Linear programming technique for multidimensional analysis of preference (LINMAP), which combines the single valued neutrosophic sets with LINMAP method. This paper establish the conventional LINMAP method to a neutrosophic MADM framework using single valued trapezoidal neutrosophic numbers and we obtain the attributes weight and ideal solution. A practical example is provided to show that our method is very effective for solving MADM problems with single valued trapezoidal neutrosophic number information. Comparative analyses with existing method are also furnished to show the advantage of our proposed method. Journal: Int. J. of Operational Research Pages: 558-577 Issue: 4 Volume: 52 Year: 2025 Keywords: single valued trapezoidal neutrosophic number; LINMAP; consistency and inconsistency measures; multi-attribute decision making; MADM. File-URL: http://www.inderscience.com/link.php?id=145241 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:52:y:2025:i:4:p:558-577 Template-Type: ReDIF-Article 1.0 Author-Name: Vadim V. Romanuke Author-X-Name-First: Vadim V. Author-X-Name-Last: Romanuke Title: Parallelisation of multiple travelling salesman problem without returning to the starting node Abstract: A method of heuristically solving the non-classic multiple travelling salesman problem is suggested, where a dramatic computational speedup is guaranteed. The salesmen covering the route must not return to the starting node in this problem. A specific genetic algorithm is the solver. To get the speedup, the nodes should be separable so that they could be divided into two or more groups. Every two adjacent groups are connected by a node called the isthmus. The respective subproblems are solved independently, in parallel, whereupon their subroutes are aggregated through the isthmuses. This shortens the aggregated route on average, although it may be slightly longer in specific cases. Such an accuracy loss is 1% to 2% in the worst case for a few hundred thousands to millions of nodes, but instead the saved computational time is counted in days, weeks, and months. The efficiency of such a parallelisation dramatically grows as more isthmuses as distinct node group separators are found. If two successive subroutes are covered by the same number of salesmen, the constraint of that every node can be visited only by one salesman is easily satisfied by correcting the subroutes at the isthmus. Journal: Int. J. of Operational Research Pages: 1-34 Issue: 1 Volume: 53 Year: 2025 Keywords: multiple travelling salesman problem; route length; genetic algorithm; parallelisation; isthmus; node group separability. File-URL: http://www.inderscience.com/link.php?id=146110 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:1:p:1-34 Template-Type: ReDIF-Article 1.0 Author-Name: P. Selvaraju Author-X-Name-First: P. Author-X-Name-Last: Selvaraju Author-Name: C.K. Sivashankari Author-X-Name-First: C.K. Author-X-Name-Last: Sivashankari Title: Effect of quadratic price-dependent demand with quadratic time-dependent demand in EOQ inventory models for deteriorative items - in fourth order equation Abstract: This research focuses on the impact of quadratic price-dependent and time-dependent demand in EOQ inventory models for deteriorative products in higher-order equations is examined in this article. Linear, constant, exponential, quadratic, stock dependent, price dependent, and other demand models have been discovered in the literature. In real practice, the price of the item and the time it takes to sell has a significant impact on the demand rate. Three models are developed: Quadratic time-dependent and price-dependent demands are used in the first model. In second model quadratic-time dependent and in the third model quadratic price dependent demands are used. The aim of this study is to identify the optimum cycle time and the optimum quantity that minimises the total cost. Each model has its own set of mathematical models. A sensitivity analysis is performed after solving and studying many numerical examples. Visual Basic 6.0 was used to create the required data. Journal: Int. J. of Operational Research Pages: 35-57 Issue: 1 Volume: 53 Year: 2025 Keywords: EOQ inventory; quadratic price-dependent demand; quadratic time-dependent demand; integrate; optimality; sensibility analysis. File-URL: http://www.inderscience.com/link.php?id=146111 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:1:p:35-57 Template-Type: ReDIF-Article 1.0 Author-Name: Anyarin Sakrujiratham Author-X-Name-First: Anyarin Author-X-Name-Last: Sakrujiratham Author-Name: Huynh Trung Luong Author-X-Name-First: Huynh Trung Author-X-Name-Last: Luong Title: A vendor-managed inventory model for deteriorating products Abstract: This paper develops a vendor-managed inventory model for deteriorating products in a two-level supply chain which is comprised of one vendor and one retailer in the case when the time to deterioration of the product follows Weibull distribution. It is assumed that the market demand is price-sensitive and shortages are fully backlogged. The proposed inventory model helps to determine the replenishment cycle length and the optimal replenishment quantity to help minimise the total cost of the entire supply chain. Numerical experiments and sensitivity analyses are conducted to illustrate the applicability of the proposed model. Some future research directions are also discussed. Journal: Int. J. of Operational Research Pages: 58-79 Issue: 1 Volume: 53 Year: 2025 Keywords: vendor-managed inventory; VMI; inventory control; deteriorating products; supply chain management. File-URL: http://www.inderscience.com/link.php?id=146112 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:1:p:58-79 Template-Type: ReDIF-Article 1.0 Author-Name: Bakhtiar Ostadi Author-X-Name-First: Bakhtiar Author-X-Name-Last: Ostadi Author-Name: Masoud Sadri Author-X-Name-First: Masoud Author-X-Name-Last: Sadri Author-Name: Ehsan Nikbakhsh Author-X-Name-First: Ehsan Author-X-Name-Last: Nikbakhsh Title: A novel hybrid BSC-DEA model for performance assessment in knowledge enterprises using balanced scorecard and data envelopment analysis approach Abstract: The importance of knowledge enterprises (knowledge-based companies) in countries' economies and their role in GDP has recently increased, and many efforts have been made to achieve a comprehensive and consistent benchmark and model for evaluating these companies. Therefore, the purpose of this paper is to provide a hybrid model for performance assessment in knowledge enterprises. So, the primary indicators have been extracted by reviewing the literature and structure of knowledge enterprises. After collecting data from knowledge enterprises and combining the balanced scorecard (BSC) and data envelopment analysis (DEA) approach, a hybrid BSC-DEA model developed to assess the partial efficiency of each unit and the total efficiency of each knowledge enterprises. Finding mentioned that the ability of start-ups and knowledge enterprises to be compared with large and old ones. Also, there will be no significant difference in the performance of companies with respect to their type. Journal: Int. J. of Operational Research Pages: 100-117 Issue: 1 Volume: 53 Year: 2025 Keywords: performance assessment; knowledge enterprises (knowledge-based companies); data envelopment analysis; DEA; balanced scorecard; BSC. File-URL: http://www.inderscience.com/link.php?id=146113 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:1:p:100-117 Template-Type: ReDIF-Article 1.0 Author-Name: Massimiliano Caramia Author-X-Name-First: Massimiliano Author-X-Name-Last: Caramia Author-Name: Emanuele Pizzari Author-X-Name-First: Emanuele Author-X-Name-Last: Pizzari Title: Waste management by bilevel optimisation: a survey Abstract: Waste management is a complex and broad field of research. Several decision-makers have conflicting objectives and hierarchies in problems falling under this category. Therefore, the common single-objective or multi-objective optimisation approaches may fail to capture the nuances of the situation. Hierarchical problems are best handled from a mathematical optimisation point of view via bilevel programming. In this paper, we survey contributions modelling waste management issues employing bilevel optimisation, a relatively new yet promising field of research. We start by providing a general analysis of these contributions and then describe the latter in macro-subjects. Finally, we draw some conclusions by providing open problems and follow-ups. Journal: Int. J. of Operational Research Pages: 80-99 Issue: 1 Volume: 53 Year: 2025 Keywords: bilevel optimisation; waste management; literature review. File-URL: http://www.inderscience.com/link.php?id=146114 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:1:p:80-99 Template-Type: ReDIF-Article 1.0 Author-Name: Khodabaccus Noorshanaaz Author-X-Name-First: Khodabaccus Author-X-Name-Last: Noorshanaaz Author-Name: Aslam Aly El-Faidal Saib Author-X-Name-First: Aslam Aly El-Faidal Author-X-Name-Last: Saib Title: Energy demand forecasting using a novel optimised Fourier grey Markov-based approach Abstract: Energy supply affects the sustainable development of an economy, hence making its modelling and forecasting crucial to policymakers. Conventional statistical models often require either prior assumptions on the distribution of the data or large historical datasets. This paper proposes the optimised Fourier-Markov grey model (OFGM), which alleviates the former two assumptions. Two test scenarios are proposed for assessing the model's performance: data prior to the COVID-19 pandemic (2010-2019) and data extending over the pandemic period (2010-2020). Numerical experiments demonstrate that the proposed algorithm very well models both scenarios and a significant improvement in the prediction accuracy is achieved. Journal: Int. J. of Operational Research Pages: 118-134 Issue: 1 Volume: 53 Year: 2025 Keywords: grey prediction model; Fourier; Markov; metaheuristic algorithm; energy forecasting. File-URL: http://www.inderscience.com/link.php?id=146115 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:1:p:118-134 Template-Type: ReDIF-Article 1.0 Author-Name: Anindita Desarkar Author-X-Name-First: Anindita Author-X-Name-Last: Desarkar Author-Name: Aaditya Umasankar Author-X-Name-First: Aaditya Author-X-Name-Last: Umasankar Author-Name: Viswa Janith Paidisetty Author-X-Name-First: Viswa Janith Author-X-Name-Last: Paidisetty Author-Name: Abhishek Sarma Author-X-Name-First: Abhishek Author-X-Name-Last: Sarma Author-Name: Annabattula Venkata Varaha Santosh Kumar Author-X-Name-First: Annabattula Venkata Varaha Santosh Author-X-Name-Last: Kumar Author-Name: Vishwanathan Raman Author-X-Name-First: Vishwanathan Author-X-Name-Last: Raman Author-Name: Mahesh Mahajan Author-X-Name-First: Mahesh Author-X-Name-Last: Mahajan Title: Optimising production and operational cost in a limestone mine by MINLP approach: an end-to-end case study Abstract: Prediction is always a challenging task; it gets harder especially in mining where lots of complexities and uncertainties are present in the system. Optimising the production output by adhering to the ore quality, minimising fuel consumption towards operational cost reduction, maximising utilisation and minimising the idle time of the fleets are a few major goals in the mining industry. However, all these things depend upon the optimal distribution of resources and equipment in appropriate places. Though manual allocation can be one solution, optimal result is not always achieved because it is difficult to optimise so many parameters on a day-to-day basis. The present research proposes a multistage and multi-objective optimisation approach based on mixed integer nonlinear programming to achieve the aforesaid goals. The experimental results show the efficacy of the method, and it is also implemented in one real mine scenario where all the above-mentioned goals are achieved. Journal: Int. J. of Operational Research Pages: 135-161 Issue: 2 Volume: 53 Year: 2025 Keywords: optimisation; mixed-integer nonlinear programming; production maximisation; fuel minimisation; resource allocation; utilisation; productivity; truck dispatching. File-URL: http://www.inderscience.com/link.php?id=146893 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:2:p:135-161 Template-Type: ReDIF-Article 1.0 Author-Name: C.K. Sivashankari Author-X-Name-First: C.K. Author-X-Name-Last: Sivashankari Author-Name: R. Valarmathi Author-X-Name-First: R. Author-X-Name-Last: Valarmathi Title: A production model for deteriorative items with time dependent demand and possible adjustment of the production rate Abstract: In this paper, two different rates of production problem of production inventory system for deteriorative items having constant demand, linear demand as well as quadratic demand is considered and in order to cut costs, it is preferable to begin production at a low rate (<i>X</i><SUB align="right"><SMALL>1</SMALL></SUB>) and gradually increase to a higher rate (<i>X</i><SUB align="right"><SMALL>2</SMALL></SUB>) over time. This is because starting with a low rate of production prevents an excessive quantity of manufactured goods from being stored at the outset. There will be three models created: constant demand in the first model, linear demand in the second model, and quadratic demand in the third model. Mathematical model is constructed for every model, as well as ideal manufacturing lot size is then determined in order to reduce overall costs. Worked-out example are provided that we then validate quantitatively. Microsoft Visual Basic 6.0 was used to write the code for this model's outcome validation. Journal: Int. J. of Operational Research Pages: 162-191 Issue: 2 Volume: 53 Year: 2025 Keywords: constant demand; linear demand; quadratic demand; two rates of productions; optimality; comparative study. File-URL: http://www.inderscience.com/link.php?id=146894 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:2:p:162-191 Template-Type: ReDIF-Article 1.0 Author-Name: Nistha Dubey Author-X-Name-First: Nistha Author-X-Name-Last: Dubey Author-Name: Ajinkya Tanksale Author-X-Name-First: Ajinkya Author-X-Name-Last: Tanksale Title: Multi-objective optimisation of surplus food recovery and redistribution units in India Abstract: Food banks are not-for-profit organisations that collect surplus and leftover food and distribute it to unfortunate people of society with an aim to alleviate hunger. The problem can be modelled as multi depot-VRP. We endeavour three primary objectives of food banks - efficiency, effectiveness, and equity. The measure for efficiency is minimum total transportation cost, minimum total shortage for effectiveness, and minimum of the maximum shortage of network is taken for equity. This paper proposes a MILP model for multi-objective optimisation of surplus food recovery and redistribution in India. Our study is the first to evaluate Indian food banks from a multi-objective perspective. To solve the proposed problem, state-of-the-art-solver Gurobi is used for weighted sum method, augmented ∈-constraint method, and augmented weighted Tchebycheff methods. Non-dominated sorting genetic algorithm is developed to solve the larger network problems. The results of the computational experiments show significant trade-off behaviour between efficiency and effectiveness. Journal: Int. J. of Operational Research Pages: 228-254 Issue: 2 Volume: 53 Year: 2025 Keywords: food banks; vehicle routing problem; VRP; multi-depot; non-dominated sorting genetic algorithm; NSGA-II; multi-objective; split loads; India. File-URL: http://www.inderscience.com/link.php?id=146895 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:2:p:228-254 Template-Type: ReDIF-Article 1.0 Author-Name: Nerda Zura Zaibidi Author-X-Name-First: Nerda Zura Author-X-Name-Last: Zaibidi Author-Name: Syuhaddah Saiddin Author-X-Name-First: Syuhaddah Author-X-Name-Last: Saiddin Author-Name: Adyda Ibrahim Author-X-Name-First: Adyda Author-X-Name-Last: Ibrahim Author-Name: Siti Aisyah Saupi Author-X-Name-First: Siti Aisyah Author-X-Name-Last: Saupi Title: Interaction model development in determining house prices by using goal programming Abstract: The buyer, the real estate developer, and the government are typically the three main parties engaged in housing projects. The interaction between these parties affects the housing market, particularly the prices of homes. The interaction has become more difficult because of the disparities in preferences between the parties. The ideal strategy for creating a fruitful partnership between these parties is still a mystery. As a result, this study has established a decision maker interaction model for getting mutual understanding on a housing project. Goal programming and a simulation method were used in this work to develop a successful interaction model. The average dwelling price that all the parties had mutually agreed upon was represented by the mean value of RM 169,878 and it is skewed between RM 85,000 and RM 350,000. The results of this study can be used by developers in Malaysia to design homes that are affordable and appealing to buyers, preventing problems with long-term unsold homes. Journal: Int. J. of Operational Research Pages: 255-268 Issue: 2 Volume: 53 Year: 2025 Keywords: interaction model; house prices; multi-objective optimisation; goal programming. File-URL: http://www.inderscience.com/link.php?id=146896 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:2:p:255-268 Template-Type: ReDIF-Article 1.0 Author-Name: Nobar Kassabian Author-X-Name-First: Nobar Author-X-Name-Last: Kassabian Author-Name: Zakaria Hammoudan Author-X-Name-First: Zakaria Author-X-Name-Last: Hammoudan Author-Name: Olivier Grunder Author-X-Name-First: Olivier Author-X-Name-Last: Grunder Author-Name: Lhassane Idoumghar Author-X-Name-First: Lhassane Author-X-Name-Last: Idoumghar Title: Genetic and hybrid algorithms to solve the container stacking problem at Tripoli-Lebanon seaport Abstract: Several factors determined the survival of the seaport: logistics, storage and distribution. A storage strategy dependent on container stacking rules is an important factor in the competence of the container terminal. This article focuses on solving the problem of stacking incoming containers in the storage yard, taking into account several criteria regarding the port of Tripoli-Lebanon. A mathematical model with a mixed integer linear program for the container stacking problem is considered in this paper. As this problem is NP-hard, large instances cannot be solved by optimisation solvers as Gurobi. We develop four algorithms to tackle this problem: a genetic algorithm (GA), a randomised greedy algorithm (RGA), an iterated local search (ILS) and a hybridisation approach between RGA and ILS. Finally, numerical simulations prove the efficiency of the GA which produces results close to the optimal solution on real instances taken from the containers terminal for small and medium sizes. Journal: Int. J. of Operational Research Pages: 201-227 Issue: 2 Volume: 53 Year: 2025 Keywords: container stacking problem; CSP; mathematical modelling; optimisation; Gurobi optimiser; genetic algorithm; GA; randomise greedy algorithm; RGA; iterated local search; ILS; hybridisation. File-URL: http://www.inderscience.com/link.php?id=146897 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:2:p:201-227 Template-Type: ReDIF-Article 1.0 Author-Name: Srinivas Subbarao Pasumarti Author-X-Name-First: Srinivas Subbarao Author-X-Name-Last: Pasumarti Author-Name: Ansumalini Panda Author-X-Name-First: Ansumalini Author-X-Name-Last: Panda Title: Entrepreneurship sustainability prediction system: a study based on climatic changes Abstract: The present study relates to a system and method for predicting entrepreneurship sustainability which aids to develop their social and environmental responsibilities towards the society and increase their own sustainability with the available and predicted resources. The system comprises a business data module (BDM), an environmental data module (EDM), an analysing module (AM), a ranking module (RM), and a suggestion module (SM). Thus, the entrepreneur is suggested with the chances and risks in the future with the available resources in a specific geometrical region or with the changes in the environment based on the ranking allocated. Journal: Int. J. of Operational Research Pages: 192-200 Issue: 2 Volume: 53 Year: 2025 Keywords: entrepreneurship sustainability; prediction system; climatic changes; risks; decision-making; business data module; BDM; environmental data module; EDM. File-URL: http://www.inderscience.com/link.php?id=146903 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:2:p:192-200 Template-Type: ReDIF-Article 1.0 Author-Name: Bilal Kanso Author-X-Name-First: Bilal Author-X-Name-Last: Kanso Author-Name: Ali Kansou Author-X-Name-First: Ali Author-X-Name-Last: Kansou Author-Name: Adnan Yassine Author-X-Name-First: Adnan Author-X-Name-Last: Yassine Title: Metaheuristic-based approaches for the multi-centre open home healthcare routing problem Abstract: This paper presents the multi-centre open home healthcare (MC-OHHC) problem with time windows and synchronisation constraints. The MC-OHHC can be described as the problem of designing least cost routes from several centres to a set of visits, without forcing them to return to the centres. Some services require simultaneous visits by using different routes to be accomplished. The contribution of the paper is three-fold: 1) it presents the corresponding mathematical linear model; 2) it gives the results related to the CPLEX resolution and an adapted constructive heuristic solution of such a problem; 3) it provides the results related to a variable neighborhood descent algorithm, a simulating annealing algorithm and a hybrid genetic algorithm. Computational results on adapted set of benchmark instances from the literature are reported and showed that our proposed approaches are fast, efficient and competitive compared to the solutions provided by the CPLEX software. Some optimal solutions are provided in short computational times, and greatly improve the initial solutions obtained by the proposed efficient constructive method. Journal: Int. J. of Operational Research Pages: 287-309 Issue: 3 Volume: 53 Year: 2025 Keywords: home healthcare problem with multi-centres; window time; synchronisation; constructive heuristic; variable neighbourhood descent metaheuristic; simulating annealing metaheuristic; hybrid genetic metaheuristic. File-URL: http://www.inderscience.com/link.php?id=146923 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:3:p:287-309 Template-Type: ReDIF-Article 1.0 Author-Name: Christopher Gaffney Author-X-Name-First: Christopher Author-X-Name-Last: Gaffney Title: The reduction of realised variance in deductible insurance Abstract: We derive a series of mathematical identities that connect insurance purchasers with insurance companies. In particular, we focus on the way in which variance is shared between the parties. We argue that, from the perspective of governmental oversight, a desirable property of insurance is that the total amount of variance experienced by the involved parties is smaller under an insurance contract than in the uninsured case. It is shown that this always holds in the case of a single insurer and a single insured, while for the case of a single insurer and multiple insured, we derive a condition which guarantees the relationship. Journal: Int. J. of Operational Research Pages: 310-323 Issue: 3 Volume: 53 Year: 2025 Keywords: deductible insurance; Affordable Care Act; ACA; insurance coverage; mean-variance analysis; variance reduction. File-URL: http://www.inderscience.com/link.php?id=146924 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:3:p:310-323 Template-Type: ReDIF-Article 1.0 Author-Name: S. Palaniammal Author-X-Name-First: S. Author-X-Name-Last: Palaniammal Author-Name: S. Pradeep Author-X-Name-First: S. Author-X-Name-Last: Pradeep Title: A state dependent arrival analysis in a non-Markovian bulk queue with server failures Abstract: Breakdown brings a huge impact in the queueing system, which causes complicated consequences. This paper comprises the results of functioning and malfunctioning of the queueing system due to continuous server breakdown. This work examines the failure of the server without interruption in state-dependent arrivals and numerous vacations. Even if a failure happens, the server is not stopped for maintenance before finishing a batch of service. The queue size PGF at an irrational time period, as well as the probability generating functions of vacation, service, and renovation completion epochs, are derived using the additional variable technique. The queueing system's unique qualities and key features are provided, along with a cost model. An extensive numerical research is done using real-world examples. Journal: Int. J. of Operational Research Pages: 324-340 Issue: 3 Volume: 53 Year: 2025 Keywords: state dependent arrivals; server breakdown; supplementary variable method; queue; bulk service; multiple vacations; cost model. File-URL: http://www.inderscience.com/link.php?id=146925 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:3:p:324-340 Template-Type: ReDIF-Article 1.0 Author-Name: Sreekanth Kolledath Author-X-Name-First: Sreekanth Author-X-Name-Last: Kolledath Author-Name: Kamlesh Kumar Author-X-Name-First: Kamlesh Author-X-Name-Last: Kumar Title: Performance analysis for F-policy machine repair problem with unreliable server balking, working breakdown and retention Abstract: In this paper we study the controlled arrival of machine repair problem with balking, working breakdowns, reneging, and retention of failed machines. Failure times and service times of operating machines are assumed to follow the exponential distribution. When the service station works in normal mode, it is subject to breakdowns while a breakdown occurs, the service station requires repair by the repairing facility. The service station's breakdown and repair times are also presumptively exponentially distributed. Additionally, it is assumed that during a breakdown period of the service station, the service station may allow to provide service to the failed machines with slower service rate. The Runge-Kutta method (4, 5) has been employed to obtain the transient behaviour of the machine repair model. Several system governing performance measures are calculated. A cost function is constructed and also the sensitivity analysis is performed to explore the effect of different parameters. Journal: Int. J. of Operational Research Pages: 341-364 Issue: 3 Volume: 53 Year: 2025 Keywords: unreliable server; F-policy; working breakdown; balking; retention. File-URL: http://www.inderscience.com/link.php?id=146926 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:3:p:341-364 Template-Type: ReDIF-Article 1.0 Author-Name: Sapan Kumar Das Author-X-Name-First: Sapan Kumar Author-X-Name-Last: Das Author-Name: Rajeev Prasad Author-X-Name-First: Rajeev Author-X-Name-Last: Prasad Author-Name: Tarni Mandal Author-X-Name-First: Tarni Author-X-Name-Last: Mandal Author-Name: Seyyed Ahmad Edalatpanah Author-X-Name-First: Seyyed Ahmad Author-X-Name-Last: Edalatpanah Title: An approach for solving fully fuzzy linear fractional transportation problem with the using of splitting technique Abstract: This paper deals with an application of splitting technique to LFP problem including fuzzy coefficients (FC). This article mainly establishes and applies a modified form of splitting technique and ranking function for solving fully fuzzy linear fractional programming (FFLFP) problem. Here, we propose a method for solving for solving FFLFP problem with the help of splitting technique. After utilising the splitting technique, the problem is converted into equivalent fully fuzzy non-linear fractional programming (FFNLFP) problem and solved the problem with the help of ranking function. The proposed algorithm is tested with three types of problems. A real life diet example (data was collected from TATA-Main Hospital, Jamshedpur, India) is first used. Then, random problem instances are generated and finally, the benchmark problems addressed in literature are also considered. In all the three cases, the results are compared with earlier reported algorithms in the literature and the computational results reveal that the proposed algorithm is competent. Journal: Int. J. of Operational Research Pages: 392-416 Issue: 3 Volume: 53 Year: 2025 Keywords: fully fuzzy linear fractional programming; FFLFP; crisp non-linear programming; fuzzy arithmetical; ranking function. File-URL: http://www.inderscience.com/link.php?id=146929 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:3:p:392-416 Template-Type: ReDIF-Article 1.0 Author-Name: Sriparna Chowdhury Author-X-Name-First: Sriparna Author-X-Name-Last: Chowdhury Author-Name: Prokash Mondal Author-X-Name-First: Prokash Author-X-Name-Last: Mondal Author-Name: Sanat Kumar Majumder Author-X-Name-First: Sanat Kumar Author-X-Name-Last: Majumder Author-Name: Pritha Das Author-X-Name-First: Pritha Author-X-Name-Last: Das Author-Name: Kajal De Author-X-Name-First: Kajal Author-X-Name-Last: De Title: Role of time dependent parabolic demand for deteriorating items and time dependent partial back order in an EOQ model of seasonal fruits under intuitionistic fuzzy environment Abstract: This study stimulates a major business factor for seasonal retailers and farmers that meet big goals by minimising the total inventory cost of seasonal agro products. At the rising of every season, demands start with shortages, and it takes time to fully filled a prime time. After that, a fresh order is placed to meet demand and deterioration for the remaining time. So, the model designed here stands with its implementation in a manufacturing concern. Here, we introduced an economic order quantity (EOQ) model with a time-dependent parabolic demand and constant deterioration rates, shortages allowed with payment delays, and a partial backorder. For a more realistic feeling, the uncertainty occurs, the model is simultaneously constructed under a crisp and intuitionistic fuzzy environment the trade credit policy up to stock-out time is planned for both cases. The numerical example and the sensitivity analysis have been done for both environments. Journal: Int. J. of Operational Research Pages: 365-391 Issue: 3 Volume: 53 Year: 2025 Keywords: economic order quantity; EOQ; seasonal agro products; deterioration; intuitionistic fuzzy; trade credit policy; partial backorder. File-URL: http://www.inderscience.com/link.php?id=146937 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:3:p:365-391 Template-Type: ReDIF-Article 1.0 Author-Name: Fernanda Salazar Author-X-Name-First: Fernanda Author-X-Name-Last: Salazar Author-Name: Ramiro Torres Author-X-Name-First: Ramiro Author-X-Name-Last: Torres Title: Mixed integer programming formulations for multi-depot bus scheduling problem in Quito Abstract: In this work the multi-depot bus scheduling problem is considered. The problem consists in assigning a set of timetabled trips characterised by an origin depot with a departure time as well as a destination depot with an arrival time to feasible bus routes. Moreover, the selected bus routes must satisfy that each trip is covered exactly by one route, each bus has to return back to its original depot at the end of the working day, the available heterogeneous bus fleet is not exceeded and a certain cost function is minimised. Two different linear integer programming formulations are proposed. The first approach is closely related to arc-based models where all possible compatible trip connections are considered explicitly leading to a multi-commodity flow formulation, whereas the latter is defined on a time-space network based on aggregation of possible connection arcs allowing to route several trips on one single arc simultaneously, which avoids the explosive increase of the model size with a growing timetable. Some lower bounds are provided for both formulations and computational results based on simulated and real-world instances are reported. Journal: Int. J. of Operational Research Pages: 269-286 Issue: 3 Volume: 53 Year: 2025 Keywords: integer programming; vehicle scheduling problem; public transportation. File-URL: http://www.inderscience.com/link.php?id=146962 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:3:p:269-286 Template-Type: ReDIF-Article 1.0 Author-Name: Vibha Verma Author-X-Name-First: Vibha Author-X-Name-Last: Verma Author-Name: Sameer Anand Author-X-Name-First: Sameer Author-X-Name-Last: Anand Author-Name: Hoang Pham Author-X-Name-First: Hoang Author-X-Name-Last: Pham Author-Name: Anu Gupta Aggarwal Author-X-Name-First: Anu Gupta Author-X-Name-Last: Aggarwal Title: Impact of time-dependent environmental factor on software release planning Abstract: Reliability assessment of software during operational phase is critical for release and warranty decisions because users are concerned about software performance during usage period. To characterise the distinctions in the settings during the testing and operational phase an environmental factor is introduced in release planning problem. It represents the impact of the usage frequency on software performance and the relative severity of the phases. In this paper, the effect of a constant environmental factor (during the warranty phase) and a time-dependent environmental factor (during the post-warranty phase) on reliability and release decisions have been analysed. A software cost model has been formulated that minimises the development cost and determines optimal variable values (testing and warranty time) while achieving reliability requirements incorporating environmental factor in the release model. The impact of changes in reliability requirements cost components, and environmental factor on the release schedule has been studied using real-life fault datasets. Journal: Int. J. of Operational Research Pages: 417-449 Issue: 4 Volume: 53 Year: 2025 Keywords: software release decisions; time-dependent environmental factor; warranty phase; testing phase; operational phase; development cost. File-URL: http://www.inderscience.com/link.php?id=147784 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:4:p:417-449 Template-Type: ReDIF-Article 1.0 Author-Name: C.K. Sivashankari Author-X-Name-First: C.K. Author-X-Name-Last: Sivashankari Author-Name: T. Nithya Author-X-Name-First: T. Author-X-Name-Last: Nithya Title: Optimal inventory and pricing for EOQ inventory model with price-dependent demand and exponential demand - in third order equation Abstract: In the present work, an optimal lot size and optimal pricing with price-dependent and exponential demand for deteriorative items in third order equations is developed and also a special case for predetermined price is also considered. Optimal lot size and price are two decision variables in this paper and optimal cycle time is a decision variable in special case of this paper. The breakeven price is considered, and the law of demand is proved. There are two models designed: the first model utilises an inventory model with optimum output and price in third order equation and the second model uses optimal cycle time of an inventory model for determining the price-breakeven point. But to my knowledge, no authors developed models for optimal pricing, and optimal lot size policies in price dependent and exponential demand in a third-order equation. This aims to obtain optimal lot size as well as pricing for overall maximum profits. The essential, as well as sufficient mathematical models are developed. Several examples, numerical in nature, are offered to achieve model validation. Additionally, a sensitivity analysis is carried out in conjunction with the representation's building blocks. Microsoft Visual Basic 6.0 was used to program the model's outcome validation. Journal: Int. J. of Operational Research Pages: 450-473 Issue: 4 Volume: 53 Year: 2025 Keywords: EOQ; optimality; price-dependent demand; exponential time-dependent demand; sensitivity analysis; cycle time. File-URL: http://www.inderscience.com/link.php?id=147785 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:4:p:450-473 Template-Type: ReDIF-Article 1.0 Author-Name: Lijian Xiao Author-X-Name-First: Lijian Author-X-Name-Last: Xiao Author-Name: Shuai Wang Author-X-Name-First: Shuai Author-X-Name-Last: Wang Author-Name: Xinhui Zhang Author-X-Name-First: Xinhui Author-X-Name-Last: Zhang Title: Data mining techniques and mathematical models for the optimal problem at a state public university Abstract: This paper studies the optimal allocation problem of financial aid: the allocation of the appropriate levels of scholarships to the correct students, as observed in a state university. This research applies data mining techniques and mathematical models to solve the optimal financial aid allocation problems in three steps. First, data mining techniques, such as logistic regression, are used to determine the matriculation and graduation probabilities associated with students from various socioeconomic backgrounds and given levels of scholarship. Second, based on the responses to the different scholarship levels, an integer programming model is developed to maximise revenue over the students' course of study. Third, decision tree and piecewise linear regression methods are employed to transform the results from the optimisation model into effective policies for implementation. This research has led to a scholarship redesign, a straightforward scholarship award policy, based on a composite GPA and ACT score, been implemented. Journal: Int. J. of Operational Research Pages: 499-524 Issue: 4 Volume: 53 Year: 2025 Keywords: financial aid allocation; optimisation; data mining; logistic regression; integer programming; decision tree. File-URL: http://www.inderscience.com/link.php?id=147786 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:4:p:499-524 Template-Type: ReDIF-Article 1.0 Author-Name: Vimlesh Kumar Ojha Author-X-Name-First: Vimlesh Kumar Author-X-Name-Last: Ojha Author-Name: Sanjeev Goyal Author-X-Name-First: Sanjeev Author-X-Name-Last: Goyal Author-Name: Mahesh Chand Author-X-Name-First: Mahesh Author-X-Name-Last: Chand Title: Data-driven approaches for decision-making in advanced manufacturing systems: a systematic literature review Abstract: Rapid automation in advanced manufacturing systems enable them to capture, store and analyse data and adopt data-driven decision-making techniques. This study investigates the applications of data-driven techniques like big data analytics, AI, and ML in advanced manufacturing systems for decision-making. The paper identifies the various factors that affect the adoption of data-driven manufacturing techniques and reviews the framework strategies for their adoption. Applications of data-driven techniques in manufacturing, such as predictive maintenance, fault analysis, forecasting, and quality improvement, are discussed in detail. The authors also highlight the challenges associated with implementing data-driven decision-making (DDDM) in the manufacturing industry, such as data quality, privacy concerns and skilled workforce requirements. The study concludes that DDDM in AMS increases productivity, reduces operational costs, improves manufacturing operations and increases competitiveness. However, further research is needed to address the identified challenges and develop effective DDDM implementation strategies in AMS. Journal: Int. J. of Operational Research Pages: 474-498 Issue: 4 Volume: 53 Year: 2025 Keywords: big data; IoT; decision-making; manufacturing; data analysis; automation; industrialisation; systematic review; data-driven decision-making; DDDM. File-URL: http://www.inderscience.com/link.php?id=147787 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:4:p:474-498 Template-Type: ReDIF-Article 1.0 Author-Name: Gurunathan Anandh Author-X-Name-First: Gurunathan Author-X-Name-Last: Anandh Author-Name: Shanmugam PrasannaVenkatesan Author-X-Name-First: Shanmugam Author-X-Name-Last: PrasannaVenkatesan Author-Name: Mark Goh Author-X-Name-First: Mark Author-X-Name-Last: Goh Author-Name: Gyan Chandra Kushwaha Author-X-Name-First: Gyan Chandra Author-X-Name-Last: Kushwaha Title: Optimising end-of-life laptop remanufacturing decisions using meta-heuristics Abstract: As the lifecycle of a laptop gets shorter, the world should expect more end-of-life (EOL) laptops. Remanufacturing of laptops is viewed as the best EOL alternative for environmental and societal reasons. This research uses a multi-period nonlinear integer programming model to decide the best EOL options for the remanufactured laptop parts based on their quality. Discrete particle swarm optimisation (DPSO) and genetic algorithm (GA) are implemented as a decision support tool in Microsoft Excel to yield the near-optimal solution. Numerical tests are conducted to compare the effectiveness of the two algorithms. For small-sized problems, the solution of the algorithms is compared with the global optimal solution obtained by the full enumeration method. For large problem instances, the solution obtained using the algorithms is compared with each other. A sensitivity analysis is performed to study the impact of the shortage and repair costs and demand on profit. Journal: Int. J. of Operational Research Pages: 525-555 Issue: 4 Volume: 53 Year: 2025 Keywords: WEEE; end of life laptop; remanufacturing; discrete particle swarm optimisation; DPSO; genetic algorithm; GA; nonlinear integer programming. File-URL: http://www.inderscience.com/link.php?id=147789 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:53:y:2025:i:4:p:525-555 Template-Type: ReDIF-Article 1.0 Author-Name: Adebayo Adedugba Author-X-Name-First: Adebayo Author-X-Name-Last: Adedugba Author-Name: Daniel Inegbedion Author-X-Name-First: Daniel Author-X-Name-Last: Inegbedion Title: RETRACTED ARTICLE Inventory control optimisation: the dynamics of deterministic request model of pharmaceutical appropriation and storage Abstract: It is the policy of Inderscience Publishers to retract from publication any paper if, subsequent to publication, it becomes a matter of dispute regarding intellectual property, publishing ethics or legal issues. Each case is judged according to individual circumstances. In this case, the author's (Adedugba Adebayo) earlier published paper 'Dynamics Of Finished Goods Inventory Control Framework: A Deterministic Request In Product Appropriation', has some substantial similarities with a work by the same author and Daniel Inegbedion, 'Inventory control optimisation: the dynamics of deterministic request model of pharmaceutical appropriation and storage' published in IJOR V54 N1, which deem it liable to a breach of ethics. This second paper has therefore been retracted. Journal: Int. J. of Operational Research Pages: 33-50 Issue: 1 Volume: 54 Year: 2025 Keywords: control; inventory chain; request; optimality; pharmaceutical organisation; models. File-URL: http://www.inderscience.com/link.php?id=148407 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:1:p:33-50 Template-Type: ReDIF-Article 1.0 Author-Name: Zeynep Ilhan Author-X-Name-First: Zeynep Author-X-Name-Last: Ilhan Author-Name: Veysel Yilmaz Author-X-Name-First: Veysel Author-X-Name-Last: Yilmaz Author-Name: Kasirga Yildirak Author-X-Name-First: Kasirga Author-X-Name-Last: Yildirak Title: Analysis of copula based variable clustering techniques and application of mortality estimation Abstract: This paper aims at developing different mortality estimation models in MIMIC-III dataset. One of the aims of the study is to bring an efficient technical proposal to determine the dependency structures between the variables. The study is conducted with 38,015 adult intensive care patients in the MIMIC-III database. The dependency structure between the variables is determined and divided into clusters with CoClust and tail dependency. With logistic regression analysis applied through clusters, the number of significant and appropriate models for death variable within 24 hours was four while there were five for death variable in the hospital. When the obtained models were analysed with error matrix, cross validity criterion and ROC curve, three valid models were obtained for the death variable within 24 hours and two for the death variable in the hospital. Journal: Int. J. of Operational Research Pages: 18-32 Issue: 1 Volume: 54 Year: 2025 Keywords: copula; CoClust; clustering with tail dependency; logistic regression analysis; mortality estimation. File-URL: http://www.inderscience.com/link.php?id=148408 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:1:p:18-32 Template-Type: ReDIF-Article 1.0 Author-Name: Sephali Mohanty Author-X-Name-First: Sephali Author-X-Name-Last: Mohanty Author-Name: Trailokyanath Singh Author-X-Name-First: Trailokyanath Author-X-Name-Last: Singh Title: A model on an optimal ordering policy for deteriorating items with exponential declining ramp-type demand, variable deterioration and shortages Abstract: The main objective of the proposed paper is to extend Sanni and Chukwu's (2013) model with the incorporation of the following characteristics: 1) inventory system deals with a single type of item; 2) demand is a generalised demand pattern and is an exponential declining ramp-type function of time; 3) deteriorating items follow a variable deterioration rate where deterioration rate is a linear increasing function of time; 4) shortages in the developed system are assumed to be a natural phenomenon; 5) only complete backlogging case has been taken into consideration. The demand rate is deterministic: it varies with respect to time up to a certain fixed point, becomes steady and then, it is fully backlogged. A couple of numerical examples are used to study the effectiveness of decision variables in the model. Finally, sensitivity analysis of the optimal solution with respect to several system parameters of the model is examined. Journal: Int. J. of Operational Research Pages: 51-69 Issue: 1 Volume: 54 Year: 2025 Keywords: completely backlogged; deteriorating items; economic order quantity; EOQ; exponential declining ramp-type demand; shortages; variable deterioration. File-URL: http://www.inderscience.com/link.php?id=148409 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:1:p:51-69 Template-Type: ReDIF-Article 1.0 Author-Name: P. Jalapathy Author-X-Name-First: P. Author-X-Name-Last: Jalapathy Author-Name: M. Mubashir Unnissa Author-X-Name-First: M. Mubashir Author-X-Name-Last: Unnissa Title: A two-phase extended warranty strategy for new and reman products Abstract: In recent decades, waste management has attracted the attention of a substantial number of scientific and industrial firms, which paved the way for reman products. Also, reman product reliability increases significantly in the product market, and offering a warranty is the most efficient way to identify the product's quality and dependability through market sales. In this paper, a two-phase extended warranty model is offered for a new and reman product to analyse the pricing strategy of the monopolistic manufacturer. The paper develops a model framework to examine optimal prices, demands, and profits of new and reman products with an extended warranty by using the Karush-Kuhn-Tucker (KKT) condition. Further, to highlight the impact of the extended warranty, failure rates, and customer willingness on new and reman products, a numerical analysis is performed. The results reveal an insight on providing an extended warranty increases the manufacturer's profit. Journal: Int. J. of Operational Research Pages: 70-88 Issue: 1 Volume: 54 Year: 2025 Keywords: re-manufacturing; pricing strategy; extended warranty; customer utility; profit analysis. File-URL: http://www.inderscience.com/link.php?id=148410 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:1:p:70-88 Template-Type: ReDIF-Article 1.0 Author-Name: Javad Gerami Author-X-Name-First: Javad Author-X-Name-Last: Gerami Author-Name: Mohammad Reza Mozaffari Author-X-Name-First: Mohammad Reza Author-X-Name-Last: Mozaffari Author-Name: Peter Wanke Author-X-Name-First: Peter Author-X-Name-Last: Wanke Author-Name: Yong Tan Author-X-Name-First: Yong Author-X-Name-Last: Tan Title: A novel inverse DEA-R model as for decision maker's preferences Abstract: In this paper, we present an innovative inverse data envelopment analysis (DEA) approach that incorporates ratio data. The proposed model simultaneously estimates the levels of inputs and outputs of decision-making units (DMUs) based on predetermined efficiency. Additionally, the model allows for assessing the levels of inputs and outputs according to the preferences of the decision maker (DM). The proposed model is nonlinear initially, but we transform it into a linear programming model. We demonstrate that the proposed model is always feasible. For the inverse DEA ratio-based (DEA-R) process, we adopt a two-step approach. Depending on the DM's preferences, we can employ different models in the inverse DEA-R process when dealing with ratio data. To illustrate the effectiveness of our approach, we present two numerical examples in the paper. Journal: Int. J. of Operational Research Pages: 89-134 Issue: 1 Volume: 54 Year: 2025 Keywords: data envelopment analysis; DEA; ratio data; DEA-R; inverse DEA-R; input/output estimation. File-URL: http://www.inderscience.com/link.php?id=148411 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:1:p:89-134 Template-Type: ReDIF-Article 1.0 Author-Name: Atma Nand Author-X-Name-First: Atma Author-X-Name-Last: Nand Title: Deteriorating inventory management model: adapting to variable lead time and consumer-driven shortages Abstract: Nowadays, businesses work together and create supply chain alliances under a particular framework, such as vendor-managed inventory. The collaboration increases visibility, which reduces costs. It aids in enhancing the environmental performance of the supply chain. Inventory model suggested here helps managers choose the optimum inventory options while considering logistics costs. It elevates the provider to a dominant position, and clients are solely supplied by that vendor. Two models are presented in this research. In the first model, the vendor and customer are expected to make a non-collaborative decision. In the second approach, the merchant and the customer decide. This work proposes an iterative process for determining the best answer, which is then tested using numerical examples demonstrating the presented models' outcomes. The current research proposes a unique evidential theory-based technique for solving an inventory model with stochastic deterioration rates and lead times that appears in a single-vendor multi-buyer inventory system. Journal: Int. J. of Operational Research Pages: 1-17 Issue: 1 Volume: 54 Year: 2025 Keywords: supply chain management; vendor-managed inventory system; integrated inventory model; merchant-consumers model; deterioration. File-URL: http://www.inderscience.com/link.php?id=148420 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:1:p:1-17 Template-Type: ReDIF-Article 1.0 Author-Name: Ana Camilla Coelho de Macêdo Author-X-Name-First: Ana Camilla Coelho de Author-X-Name-Last: Macêdo Author-Name: Caio Bezerra Souto Maior Author-X-Name-First: Caio Bezerra Souto Author-X-Name-Last: Maior Title: Comparing classical time-series models and machine learning for demand forecast on the beverage industry in COVID-19 pandemic Abstract: Due to the growth of competitiveness in the market, demand forecasting has become a fundamental tool to manage production and identify new opportunities for the company. The fundamental goal of a series analysis is to make predictions from historical data to support decisions accurately. During the COVID-19 pandemic, the market has undergone numerous changes, and consumer needs have changed, directly affecting beverage sales. In this work, classic models of time series - Holt-Winters and ARIMA - and machine learning - support vector machines and random forests - were used to perform demand forecasts from several historical data series of a real beverage direct distribution centre located in Brazil. The data used were stratified into nine data series: 1) the total volume of beverages sold by the operation; 2) separated by type of beverage (beer and non-alcoholic beverage); 3) in six sales channels. Indeed, as the comparison considers demands before and after the pandemic (including pre-and post-vaccination), the predictions were challenging. The comparison of models considers predictions up to 15 steps (months) ahead using the RMSE and MAPE error metrics. Here, the models with the best-aggregated performances were ARIMA and SVM; however, no model was strictly better than the others. Journal: Int. J. of Operational Research Pages: 211-228 Issue: 2 Volume: 54 Year: 2025 Keywords: time series; demand forecast; beverage industry; Holt-Winters; ARIMA; support vector machine; SVM; random forest. File-URL: http://www.inderscience.com/link.php?id=148943 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:2:p:211-228 Template-Type: ReDIF-Article 1.0 Author-Name: G. Ayyappan Author-X-Name-First: G. Author-X-Name-Last: Ayyappan Author-Name: S. Meena Author-X-Name-First: S. Author-X-Name-Last: Meena Title: Analysis of MMAP/PH(1), PH(2)/1 non-preemptive priority queueing model with phase-type vacation and repair, feedback, breakdown, close-down and reneging Abstract: We consider a single server non-preemptive priority queue with phase-type vacation and repair, feedback, breakdown, close-down, and reneging. Customers arrive according to the marked Markovian arrival process and their service time according to phase-type distribution. If the high priority customers need feedback, they lose their priority and join the low priority queue. At any instant, if the server is broken down, it will immediately go into a repair process. When there are no customers present in both the queues, the server close-down the system and then goes on vacation. During the close-down and vacation period, high priority customers may renege. The matrix analytic method is used to look into the number of consumers that are currently in the system. Analysis of the steady-state, the server active period, and the total cost are all discussed. Finally, some significant performance measures and numerical examples are given. Journal: Int. J. of Operational Research Pages: 229-259 Issue: 2 Volume: 54 Year: 2025 Keywords: marked Markovian arrival process; phase-type distribution; server vacation; breakdown; repair; feedback; close-down; reneging; non-preemptive priority; matrix-analytic method. File-URL: http://www.inderscience.com/link.php?id=148945 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:2:p:229-259 Template-Type: ReDIF-Article 1.0 Author-Name: Mayank Singh Author-X-Name-First: Mayank Author-X-Name-Last: Singh Author-Name: Madhu Jain Author-X-Name-First: Madhu Author-X-Name-Last: Jain Title: Fluid approximation for a Markovian queue under disaster and reboot Abstract: A fluid approximation for the performance analysis of a Markovian disaster queue with reboot and repair is presented. During normal operation, the system may suffer disaster failure, in which case all jobs in the system will be lost. If the fault is successfully covered, the system recovers from the failure by rebooting; otherwise, the system enters a repair state, where a specialised repairman removes the fault. Analytical methods of continued fractions (CFs) and probability generating function (PGF) are used to get the probability distribution of buffer content. To analyse the fluctuation in buffer content with regard to buffer content probabilities, the numerical data is computed and displayed in the form of graphs and tables. Furthermore, numerical results obtained using analytical formulae are compared with the results obtained by adaptive neuro-fuzzy inference system (ANFIS). Journal: Int. J. of Operational Research Pages: 260-280 Issue: 2 Volume: 54 Year: 2025 Keywords: Markov fluid queue; disaster; reboot; continued fractions; ANFIS; probability generation functions. File-URL: http://www.inderscience.com/link.php?id=148946 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:2:p:260-280 Template-Type: ReDIF-Article 1.0 Author-Name: I.R. Gawai Author-X-Name-First: I.R. Author-X-Name-Last: Gawai Author-Name: D.I. Lalwani Author-X-Name-First: D.I. Author-X-Name-Last: Lalwani Title: MADEA: multi-objective amended differential evolution algorithm Abstract: The aim of the current work is to modify the amended differential evolution algorithm (ADEA) to solve multi-objective optimisation problems. The modified ADEA algorithm is named MADEA. The single objective ADEA algorithm is employed with an efficient non-dominated search (ENS) method for finding the non-dominated solutions, a crowding distance technique for comparing the non-dominated solutions, and an archive that stores the non-dominated solutions. The above-mentioned modifications in ADEA resulted in an algorithm capable of solving benchmark functions given in CEC 2009 with competitive results. The performance of the MADEA is measured using inverted generational distance (IGD) and hypervolume (HV). The outcomes of performance measures are compared against MWDEO, MOEA/D, MOPSO, SMPSO, NSGA-II, SHAMODEWO, MOEADSTM and NSGA-III. The results show that MADEA has outperformed 60% of the problems in the test suite in IGD values and the results were found to be significantly similar to 20% of the competition. Journal: Int. J. of Operational Research Pages: 135-158 Issue: 2 Volume: 54 Year: 2025 Keywords: meta-heuristics; evolutionary algorithm; differential evolution; archives; multi-objective optimisation problems; amended differential evolution algorithm; ADEA; efficient non-dominated search; ENS; inverted generational distance; IGD. File-URL: http://www.inderscience.com/link.php?id=148948 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:2:p:135-158 Template-Type: ReDIF-Article 1.0 Author-Name: Javad Gerami Author-X-Name-First: Javad Author-X-Name-Last: Gerami Author-Name: Sahar Ostovan Author-X-Name-First: Sahar Author-X-Name-Last: Ostovan Author-Name: Mohammad Reza Mozaffari Author-X-Name-First: Mohammad Reza Author-X-Name-Last: Mozaffari Author-Name: Peter Wanke Author-X-Name-First: Peter Author-X-Name-Last: Wanke Author-Name: Yong Tan Author-X-Name-First: Yong Author-X-Name-Last: Tan Title: A novel fuzzy network ASBM approach based on DEA and DEA-R models for efficiency measurement in oil refineries Abstract: In this study, we develop fuzzy network data envelopment analysis (DEA) models based on the additive slacks-based measure (ASBM) model in the presence of undesirable output. In the real world, we encounter many cases where the data are inaccurate and ratios are involved simultaneously. In this regard, we propose two new models to evaluate the efficiency of decision making units (DMUs) with a three-stage network structure in the presence of fuzzy inputs and outputs based on DEA and DEA-R models, by selecting two different strategies, external and internal. In the following, we apply the proposed approach to evaluate a set of oil refineries in Iran, and we present the results of the research. Journal: Int. J. of Operational Research Pages: 159-210 Issue: 2 Volume: 54 Year: 2025 Keywords: data envelopment analysis; DEA; efficiency; DEA-R; fuzzy network data envelopment analysis; FNDEA three-stage network. File-URL: http://www.inderscience.com/link.php?id=148952 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:2:p:159-210 Template-Type: ReDIF-Article 1.0 Author-Name: Raunaque Paraveen Author-X-Name-First: Raunaque Author-X-Name-Last: Paraveen Author-Name: Manoj Kumar Khurana Author-X-Name-First: Manoj Kumar Author-X-Name-Last: Khurana Title: Permutation flow-shop scheduling with early and late penalty costs using the Jaya algorithm Abstract: The purpose of this study is to use the most efficient meta-heuristic methodologies in permutation flow shop to identify the ideal sequence of jobs with the least amount of penalties for being early and late. The permutation flow shop is a common job shop problem in which all jobs must pass through all machines in a predefined order. Numerous meta-heuristic algorithms have been developed to tackle this problem. However, users often struggle with selecting appropriate algorithm parameters due to the problem's complexity. To address these challenges, this research adopts the recently developed Jaya algorithm, which stands out for being a parameter-less approach that aims to achieve success while avoiding failure. The Jaya algorithm was tested alongside a genetic algorithm using a simulated industry dataset. This dataset contained different scenarios with varying numbers of jobs and machines. The Jaya algorithm consistently outperformed the genetic algorithm, providing superior results for the given problem. Journal: Int. J. of Operational Research Pages: 310-333 Issue: 3 Volume: 54 Year: 2025 Keywords: permutation flow-shop scheduling; Jaya algorithm; tardiness penalties; earliness penalties. File-URL: http://www.inderscience.com/link.php?id=149656 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:3:p:310-333 Template-Type: ReDIF-Article 1.0 Author-Name: Khedidja Boughafene Author-X-Name-First: Khedidja Author-X-Name-Last: Boughafene Author-Name: Karim Abbas Author-X-Name-First: Karim Author-X-Name-Last: Abbas Title: Uncertainty quantification and global sensitivity analysis of an M/G/1 retrial queue with Bernoulli schedule Abstract: In this paper, we are interested in studying uncertainty quantification and global sensitivity analysis in retrial queueing models. Specifically, we investigate the M/G/1 retrial queue with priority customers, Bernoulli schedule and general retrial times. We develop a new methodology for integrating epistemic uncertainties into the computation of performance measures of retrial queueing models, where these measures are considered as functions of the input random parameters and approximated with polynomial chaos expansions. In order to perform global sensitivity analysis, we use Sobol' indices which allow us to make an importance ranking of parameters. In addition, we characterise statistically several performance measures, given that distribution of the model parameter expressing the uncertainty about the exact parameter value is known. Furthermore, we use the Markov inequality to assess the risk induced by working with uncertain performance measures instead of that evaluated at fixed parameters. Several numerical results are provided and compared to Monte Carlo simulations ones. Journal: Int. J. of Operational Research Pages: 281-309 Issue: 3 Volume: 54 Year: 2025 Keywords: Sobol' indices; polynomial chaos expansions; epistemic uncertainty; uncertainty quantification; risk analysis; Monte Carlo simulation; retrial queueing model. File-URL: http://www.inderscience.com/link.php?id=149657 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:3:p:281-309 Template-Type: ReDIF-Article 1.0 Author-Name: Aaishwarya Bajaj Author-X-Name-First: Aaishwarya Author-X-Name-Last: Bajaj Author-Name: Jayesh M. Dhodiya Author-X-Name-First: Jayesh M. Author-X-Name-Last: Dhodiya Title: Aspiration level-based multi-objective quasi oppositional Jaya algorithm to solve multi-objective solid travelling salesman problem with carbon emission Abstract: The multi-objective solid travelling salesman problem (MOSTSP) is a complex optimisation problem as it employs multiple conveyances while travelling. In this paper, a newly developed aspiration level-based multi-objective quasi oppositional Jaya (AL-based MOQO Jaya) algorithm is used to tackle MOSTSP addressed within a crisp environment. A real-life example of Surat City is considered for 10 and 50 nodes, with five distinct objectives: cost, time, risk, distance, and carbon emission, with carbon-constrained. The obtained outcomes are compared with the results of the hybrid genetic algorithm (HGA) and the CPLEX optimisation tool. Remarkably, the AL-based MOQO Jaya algorithm exhibits significantly low computational time as compared to CPLEX and HGA. Furthermore, the performance of the algorithm is the study using coverage. The paper, concludes that the AL-based MOQO Jaya algorithm efficiently solves the MOSTSP, with effective output and provides alternative decision-making solutions to decision-makers. Journal: Int. J. of Operational Research Pages: 372-392 Issue: 3 Volume: 54 Year: 2025 Keywords: multi-objective solid travelling salesman problem; MOSTSP; aspiration level; carbon emission; multi-objective quasi oppositional Jaya; CPLEX. File-URL: http://www.inderscience.com/link.php?id=149659 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:3:p:372-392 Template-Type: ReDIF-Article 1.0 Author-Name: Gomolemo Jacqueline Lekono Author-X-Name-First: Gomolemo Jacqueline Author-X-Name-Last: Lekono Author-Name: Thatayaone Moakofi Author-X-Name-First: Thatayaone Author-X-Name-Last: Moakofi Author-Name: Broderick Oluyede Author-X-Name-First: Broderick Author-X-Name-Last: Oluyede Author-Name: Lesego Gabaitiri Author-X-Name-First: Lesego Author-X-Name-Last: Gabaitiri Title: A new heavy-tailed Topp-Leone-G power series class of distributions with applications Abstract: We propose a new heavy-tailed distribution, namely, type I heavy-tailed Topp-Leone-G power series class of distributions. Statistical properties including quantile function, hazard rate function, probability weighted moments, distribution of order statistics and Rényi entropy are presented. Maximum likelihood estimation method is used to obtain estimates of the parameters of the new class of distributions, and Monte Carlo simulation is used to assess the consistency of the estimators. Illustration of the usefulness and applicability of the new class of distributions is done by analysing four real life datasets from different fields. Journal: Int. J. of Operational Research Pages: 334-371 Issue: 3 Volume: 54 Year: 2025 Keywords: applicability; estimation methods; heavy-tailed; power series; Topp-Leone. File-URL: http://www.inderscience.com/link.php?id=149707 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:3:p:334-371 Template-Type: ReDIF-Article 1.0 Author-Name: M.R. Ganesh Author-X-Name-First: M.R. Author-X-Name-Last: Ganesh Author-Name: B.M. Rijas Author-X-Name-First: B.M. Author-X-Name-Last: Rijas Author-Name: T. Radha Ramanan Author-X-Name-First: T. Radha Author-X-Name-Last: Ramanan Title: Design and development of an LPP model for food grain procurement: a case study Abstract: Indian public distribution system is unique in many respects. It involves various activities like paddy procurement, warehousing, transportation, processing and distribution of rice grains through fair price shops. This paper studies the present system of food grain procurement until its distribution of rice grains at FPSs and develops a conceptual model followed by a linear programming problem (LPP) model with reasonable assumptions. Based on the understanding of the existing conceptual model, the paper designs a new supply chain procurement network by integrating paddy procurement and its distribution. A mathematical model of the designed network is developed as an LPP model with the objective of minimising the transportation cost. The study's uniqueness is two-fold; firstly, the development of an LPP model for the procurement system and secondly is about proposing the fair price shops as the procurement centre instead of the existing mechanisms. The study finds that the proposed supply chain procurement network can minimise the transportation cost by 21%. Journal: Int. J. of Operational Research Pages: 393-411 Issue: 3 Volume: 54 Year: 2025 Keywords: conceptual model; network design of network; distribution; linear programming problem model; LPP; transportation cost. File-URL: http://www.inderscience.com/link.php?id=149708 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:3:p:393-411 Template-Type: ReDIF-Article 1.0 Author-Name: Javier de Prado Author-X-Name-First: Javier de Author-X-Name-Last: Prado Author-Name: Sandro Moscatelli Author-X-Name-First: Sandro Author-X-Name-Last: Moscatelli Author-Name: Pedro Piñeyro Author-X-Name-First: Pedro Author-X-Name-Last: Piñeyro Author-Name: Libertad Tansini Author-X-Name-First: Libertad Author-X-Name-Last: Tansini Author-Name: Omar Viera Author-X-Name-First: Omar Author-X-Name-Last: Viera Title: Solving the multi-depot vehicle routing problem with limited supply capacity at the depots with a multi-phase methodology Abstract: We consider an extension of the multi-depot vehicle routing problem (MDVRP), in which the supply capacity of the depots is limited. To solve this problem, we propose a multi-phase methodology, that extends the 'cluster first, route second' approach. It is based on iterative routings to find and reassign misplaced customers with respect to the depots and with the objective of improving the final routing. Several assignment and routing algorithms are considered to evaluate the proposed methodology under different settings. A mathematical model of the problem is given to perform a comparative study of the methodology against an exact solution method. We also evaluate the methodology for the MDVRP in order to provide a comparison with benchmark instances of the literature. The results obtained from the numerical experiments carried out allow to conclude that the methodology can be successfully applied to the MDVRP with capacitated depots. Journal: Int. J. of Operational Research Pages: 413-434 Issue: 4 Volume: 54 Year: 2025 Keywords: multi-depot vehicle routing problem; MDVRP; heuristics; limited supply capacity at depots; capacitated vehicles; clustering; assignment; routing; multi-phase methodology; MPM. File-URL: http://www.inderscience.com/link.php?id=150777 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:4:p:413-434 Template-Type: ReDIF-Article 1.0 Author-Name: Tuhin Bera Author-X-Name-First: Tuhin Author-X-Name-Last: Bera Author-Name: Nirmal Kumar Mahapatra Author-X-Name-First: Nirmal Kumar Author-X-Name-Last: Mahapatra Title: Threshold neutrosophic set and its application to decision making in planning and construction industry Abstract: The basic motivation of the present study is to furnish a decision making approach in soft and neutrosophic environment. The methodology is based on the notion of neutrosophic cut set. Different kind of threshold neutrosophic set and their level soft set are innovated here. Then their inter relations are also investigated. The approach is further extended over soft and weighted neutrosophic set. Suitable solution algorithms are developed in both attempts and these are demonstrated to make a decision in planning and construction industry. The outcomes are analysed and the potentiality of the proposed method is claimed after comparing the results from existing study. Journal: Int. J. of Operational Research Pages: 472-489 Issue: 4 Volume: 54 Year: 2025 Keywords: neutrosophic soft set; threshold neutrosophic set; level soft set; decision making approach. File-URL: http://www.inderscience.com/link.php?id=150778 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:4:p:472-489 Template-Type: ReDIF-Article 1.0 Author-Name: Chirag R. Trivedi Author-X-Name-First: Chirag R. Author-X-Name-Last: Trivedi Author-Name: Mrudul Y. Jani Author-X-Name-First: Mrudul Y. Author-X-Name-Last: Jani Author-Name: D.C. Joshi Author-X-Name-First: D.C. Author-X-Name-Last: Joshi Author-Name: Manish R. Betheja Author-X-Name-First: Manish R. Author-X-Name-Last: Betheja Author-Name: Nakul Rawal Author-X-Name-First: Nakul Author-X-Name-Last: Rawal Title: Optimising inventory management: addressing constant deterioration and imperfect items with screening, time-dependent demand and two-layer trade credit Abstract: Inventory models are frequently developed in which products of perfect quality are produced. The purpose of this study is to create a model with uncertain supply may have a random proportion of defective items. As a result, item inspection becomes critical in all situations, when products are vanishing current companies may use promotional tools to boost sales trade credit is a strategy that benefits both suppliers and retailers. Hence, a two-level trade credit scheme in which the supplier offers a credit period to retailer and retailer provides to customers. Inflation is the rate at which the prices for goods often affects the buying capacity of consumers and recent time value of money is calculated. The primary purpose is to enhance the retailer's overall profit with respect to cycle time and is numerically solved using a devised algorithm. Finally, sensitivity analysis is done on key parameters, and some managerial implications for the retailer are emphasised. Journal: Int. J. of Operational Research Pages: 435-471 Issue: 4 Volume: 54 Year: 2025 Keywords: deterioration; imperfect items; screening; time-dependent demand; two-layer trade credit. File-URL: http://www.inderscience.com/link.php?id=150779 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:4:p:435-471 Template-Type: ReDIF-Article 1.0 Author-Name: Daniel Morillo-Torres Author-X-Name-First: Daniel Author-X-Name-Last: Morillo-Torres Author-Name: Nicol Solarte-Herrera Author-X-Name-First: Nicol Author-X-Name-Last: Solarte-Herrera Author-Name: Maicol Narváez-Rincón Author-X-Name-First: Maicol Author-X-Name-Last: Narváez-Rincón Author-Name: Rafael Rojas-Millan Author-X-Name-First: Rafael Author-X-Name-Last: Rojas-Millan Author-Name: Gustavo Gatica Author-X-Name-First: Gustavo Author-X-Name-Last: Gatica Author-Name: Jesus Gonzalez-Feliu Author-X-Name-First: Jesus Author-X-Name-Last: Gonzalez-Feliu Title: Solving a practical examination timetabling problem via abductive reasoning and integer programming Abstract: Scheduling of examination dates is a complex process that affects student satisfaction at higher education institutions. The literature refers to this as the timetabling problem. Formally, it consists in assigning a series of events to certain timetable blocks within a given time interval, limited by a set of constraints, some of which must be strictly adhered to (hard), while others are only desirable (soft). This paper proposes and validates a mathematical model for scheduling at a university in Colombia. The main paper's contribution is that the model is aimed at improving student satisfaction compared to the scheduling performed previously by the university. The methodology is based on an abductive vision of operations research with five stages where a mixed-integer linear programming model was proposed, and it was validated in a real-life instance. The results show a 38.9% average reduction in contiguous exams. Journal: Int. J. of Operational Research Pages: 490-512 Issue: 4 Volume: 54 Year: 2025 Keywords: abductive methodology; integer programming; timetable problem; exam scheduling problem; applied case. File-URL: http://www.inderscience.com/link.php?id=150780 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:4:p:490-512 Template-Type: ReDIF-Article 1.0 Author-Name: Taquiuddin Z. Quazi Author-X-Name-First: Taquiuddin Z. Author-X-Name-Last: Quazi Author-Name: Vivek Sunnapwar Author-X-Name-First: Vivek Author-X-Name-Last: Sunnapwar Title: Evaluation of power generation units of a thermal power plant focusing on sustainability and technical attributes Abstract: Coal is the primary source for generating power across the world and it is expected that this fuel's domination would last for a few more decades. Coal-fired power generation contributes substantially to pollution, negatively impacts the natural habitat, and hampers socioeconomic aspects of the economy. Hence, there is a need to investigate the performance of the power-generating units of thermal plants based on the evaluation criteria. In this study, the evaluation attributes related to technical, economic, social, and environmental aspects have been identified through the critical literature survey and interaction with the subject matter experts of the domain. Three power units of a coal-fired power plant have been evaluated using the hybrid MCDM framework. The results of the investigation highlighted that the 'social' aspect is the most crucial and subfactors, namely 'risk related to safety', 'energy generation efficiency', and 'social acceptability' are the significant ones. Also, the power unit 'C' ranked first out of the three units under consideration. Finally, managerial, academic, and social implications are offered. Journal: Int. J. of Operational Research Pages: 529-558 Issue: 4 Volume: 54 Year: 2025 Keywords: evaluation; coal-fired power generation; sustainability; coal technologies. File-URL: http://www.inderscience.com/link.php?id=150781 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:4:p:529-558 Template-Type: ReDIF-Article 1.0 Author-Name: Neha Author-X-Name-First: Author-X-Name-Last: Neha Author-Name: Abhishek Tandon Author-X-Name-First: Abhishek Author-X-Name-Last: Tandon Author-Name: Anu G. Aggarwal Author-X-Name-First: Anu G. Author-X-Name-Last: Aggarwal Title: Impact of slippage cost and risk cost on software development under imperfect debugging environment Abstract: Computers have become an integral part of everyone's life in this modern information society, and they are especially important in several fields that save lives. Consequently, it is necessary to develop reliable and cost-efficient software systems. This study discusses a cost model that integrates slippage and risk costs and looks at how these cost factors affect the timing of software releases. The reliability growth model, which is developed by taking into account the testing coverage function in an imperfect debugging environment, is used to study the cost model. The model is validated using a real-life failure dataset and with the estimated values, we formulate an optimisation model to develop the cost model concerning reliability function. With the aid of sensitivity analysis, the study also examines the potential effects of cost variation on the overall budget and delivery schedule. Journal: Int. J. of Operational Research Pages: 513-528 Issue: 4 Volume: 54 Year: 2025 Keywords: software reliability growth model; SRGM; testing coverage; imperfect debugging; optimisation. File-URL: http://www.inderscience.com/link.php?id=150787 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijores:v:54:y:2025:i:4:p:513-528