European J. of Industrial Engineering (27 papers in press)
The impact of online sales in centralized and decentralized dual-channel supply chains
by Subrata Saha
Abstract: This paper studies a supply chain structure featuring two different types of distribution channels through which manufacturers sell products. The centralised and decentralised distribution channels considered in this study are affected by online sales outside the structured channels. In the centralised distribution channel, two retail stores located in geographically distinct markets are operated by a single owner. In the decentralised distribution channel, two retailers independently operate two retail stores. In the non-cooperative scenario, the manufacturer always prefers the decentralised distribution channel irrespective of whether an online channel is used. To achieve channel coordination, a revenue-sharing contract is applied, but it can be used to coordinate only the decentralised distribution system. Therefore, a modified revenue-sharing contract is proposed to coordinate the centralised distribution system. The analytical study reveals that without coordination among the channel members, the manufacturer always earns maximum profit in decentralised distribution systems. However, if the supply chain is coordinated, then the manufacturer receives more benefits from using the centralised distribution systems under certain conditions. Propositions are presented to describe the characteristics of distribution structures, and to provide meaningful management guidelines for coordinating them. Extensive numerical investigations are also presented.
Keywords: Supply chain management; Dual-channel supply chain; Revenue sharing contract; Pricing strategy; Stackelberg.
A Novel Two-Phase Algorithm for a Centralized Production Planning Problem by Symmetric Weighted DEA Approach: A Case Study in Energy Efficiency
by Elham Shadkam
Abstract: This paper proposes a novel two-phase algorithm for a centralised production planning problem that covers both long-term and mid-term planning simultaneously. Mid-term decisions (first phase) include determining the amount of new inputs and outputs of units in the next production period and long-term decisions (second phase) are related to planning to create a new efficient production unit. The first phase includes a data envelopment analysis approach with symmetric weights through the penalty function. The second phase includes combining data envelopment analysis and response surface methods. In order to evaluate the proposed method, the National Iranian Gas Company is considered as a real case problem. The results show the superiority of the algorithm in both phases over similar methods. The main advantage of the first phase is the realistic production plan. Also, the main advantage of the second phase is optimising the response surface functions and maximising the efficiency of the unit at the same time using one model.
Keywords: production planning; symmetric weighted approach; data envelopment analysis; DEA; response surface method; gas company.
Simultaneous Remanufacturing and Government Incentives in Remanufacturing Systems
by Mehmet ALEGOZ
Abstract: Remanufacturing has been receiving a growing attention in both academia and industry due to its economic and environmental benefits. This study investigates the effects of simultaneous remanufacturing, i.e., the effects of entrance of an actor to remanufacturing business when there is already one actor making remanufacturing. To this end, three remanufacturing systems are considered as only the manufacturer remanufactures (case 1), only the retailer remanufactures (case 2) and both the manufacturer and the retailer simultaneously remanufacture (case 3) the used products. Stackelberg Game models are proposed for each of these cases and the performances of the actors are compared. The role of the government in remanufacturing systems is also investigated and the question, to whom should the government provide incentives in order to maximise the remanufactured product quantity, is discussed. Computational results bring various managerial insights regarding the simultaneous remanufacturing decisions of the actors and the role of the government. [Submitted: 1 May 2021; Accepted: 4 October 2021]
Keywords: remanufacturing; competition; government incentive; closed-loop supply chain.
The Charging Infrastructure Design Problem with Electric Taxi Demand Prediction Using Convolutional LSTM
by Seong Wook Hwang, Sunghoon Lim
Abstract: The authors present a charging infrastructure design problem with electric taxi demand prediction. Due to environmental concerns, electric vehicle adoption has significantly increased in the transportation sector. However, the use of electric vehicles is not highly commercialised in the taxi industry, because the immature charging network and frequent charging decrease taxi revenue efficiency. Therefore, charging infrastructure needs to be built in urban areas in consideration of operational requirements of the taxi industry. The authors first design a convolutional long short-term memory model that predicts taxi demand, along with hotspots. Then, based on the predicted taxi demand in hotspots, a mixed integer linear programming model is proposed to optimise the location of recharging stations to minimise the cost of locating stations and charging service. Also, we propose a heuristic algorithm to solve realistic and practical problems. Lastly, a case study is presented to validate the proposed research. [Submitted: 28 April 2021; Accepted: 5 September 2021]
Keywords: OR in service industries; transportation; heuristics; machine learning; artificial intelligence.
Solving airline crew pairing problems through constraint partitioning
by Maryam Radman, Kourosh Eshghi
Abstract: In this paper, a decomposition technique based on constraint partitioning is developed to solve the crew pairing problem (CPP) which has an overriding importance in the airline industry as it determines the crew cost. The method is based on the observation that in large-scale problems the constraints can be partitioned to some sub-problems which involve special subsets of variables. The resultant structure is called the
Keywords: crew pairing problems; CPPs; constraint partitioning; decomposition technique; sub-problem; airline industry.
An integrated Markov chain model for the economic-statistical design of adaptive multivariate control charts and maintenance planning
by Jalal Taji, Hiwa Farughi, Hasan Rasay
Abstract: In this paper, the mean of a process with several quality characteristics is monitored using a multivariate control chart which is a variable parameter (Vp) chi-square control chart with two types of sampling schemes. For this purpose, using the property of Markov chains, an integrated model is developed that coordinates the decisions related to the economic-statistical design of the control chart and maintenance planning. In the case of failure, the system will shut down automatically and a corrective maintenance activity will be performed immediately. Preventive maintenance activity is implemented when an out-of-control state is correctly identified. To evaluate the economic efficiency of the proposed model, a comparison between its optimum cost and the optimum cost of a multivariate exponentially weighted moving average (MEWMA) control chart and also a model that applies a chi-square control chart with fixed parameter is provided. Moreover, constraints related to ARL0 and ARL1 have been taken into account to ensure the statistical performance of the model. The results of the numerical analyses show a significant improvement in the cost per time unit. [Submitted: 23 November 2020; Accepted: 28 November 2021]
Keywords: integrated model; quality control; chi-square control chart; maintenance planning.
Critical factors for sustaining Lean Manufacturing in the long term: a multimethod study
by Natalia R. Lopes, Moacir Godinho Filho, Gilberto Miller Devós Ganga, Guilherme Tortorella, Mario H. B. M. Callefi, Bruna Lima
Abstract: In recent years, lean manufacturing (LM) has been used to improve the operational performance of organisations by improving the productivity, quality and profitability of their operations. However, some authors claim that these organisations are struggling to implement and maintain lean initiatives in a sustainable way over time. This paper proposes a list of critical factors for sustaining LM in the long-term. We used a multi-method research approach. First, we generated a list of critical factors for sustaining LM in the long-term using the systematic literature review approach. Subsequently, interviews with experts were used to refine these factors. Following this, two case studies were performed, and the results passed through another round of interviews with experts to ensure the robustness of the results. The main result of the research is a list of 19 LM sustainability factors. To the best of the authors knowledge, this is the first research to propose a scientifically validated list of critical factors for sustaining LM. The contribution of this work lies in consolidating the lean sustainability factors widely found in the literature. In practical terms, the proposed list can guide managerial efforts towards sustaining lean in the long-term. [Received: 22 April 2021; Accepted: 29 December 2021]
Keywords: lean; lean manufacturing; sustainability; multi-method research; continuous improvement.
A PARTIAL COVERAGE HIERARCHICAL LOCATION ALLOCATION MODEL FOR HEALTH SERVICES
by Orhan Karasakal, Esra Koktener Karasakal, Özgün Töreyen Öztürk
Abstract: We consider a hierarchical maximal covering location problem (HMCLP) to locate health centres and hospitals so that the maximum demand is covered by two levels of services in a successively inclusive hierarchy. We extend the HMCLP by introducing the partial coverage and a new definition of the referral. The proposed model may enable an informed decision on the healthcare system when dynamic adaptation is required, such as a COVID-19 pandemic. We define the referral as coverage of health centres by hospitals. A hospital may also cover demand through referral. The proposed model is solved optimally for small problems. For large problems, we propose a customised genetic algorithm. computational study shows that the GA performs well, and the partial coverage substantially affects the optimal solutions. [Submitted: 20 January 2021; Accepted: 15 January 2022]
Keywords: hierarchical maximal covering location problem; partial coverage; gradual coverage; referral; heuristics; genetic algorithm.
Risk-Averse Joint Facility Location-Inventory Optimization for Green Closed-Loop Supply
by Guodong Yu, Pengcheng Dong, Ying Xu, Xiao Zhao
Abstract: This paper considers a joint facility location-inventory optimisation for green closed-loop supply chain network design under demand uncertainty. Under the uncoordinated inventory policy, we propose a chance-constrained risk-averse bi-objective 01 mixed-integer nonlinear stochastic programming to minimise the total expected cost and CO2 emissions. To solve the model, we first present an equivalent reformulation with a single objective based on distributionally robust optimisation. Then, we provide a linear reformulation with some valid inequalities. We also provide a greedy heuristic decomposition searching rule to solve the large-scale problem. We finally present a numerical analysis to show the performance of our methods. Results illustrate that the risk-averse joint model can effectively improve service capability and reliability than independent and risk-neutral location and inventory problems. We also recommend that the incompletely uncoordinated strategy for the joint optimisation can be more cost-effective and generate fewer workloads. Besides, the proposed algorithm achieves a more desirable performance than CPLEX for large-scale problems.
Keywords: green closed-loop supply chain; facility location; inventory; risk-averse; chance constraint; distributionally robust optimisation.
A stochastic mixed-integer model to support foodbank resources prepositioning during the prelude to a natural disaster
by ADRIAN RIVERA, Neale Smith, Esteban Ogazon, Angel Ruiz Bartolome
Abstract: A key strategic issue in pre-disaster planning for humanitarian logistics is the pre-establishment of adequate capacity and resources that enable ef?cient relief operations. Foodbanks must review their decisions and replan their activities upon the arrival of catastrophic events, such as earthquakes or floods. With the aim to support managers in the adaptation of their network and preparedness decisions during the prelude to the event, this paper presents a scenario-based stochastic mixed-integer optimisation formulation that aims to minimise the maximum amount of unfulfilled relief needs considering uncertainty both on the demand as well as on the availability of the infrastructure. The formulation was applied to the case of hurricane Odile that struck the Baja California Peninsula, Mexico, in 2014. Numerical experiments demonstrate that the solution reached by the proposed mathematical formulation improved the actual decisions that were made during the event. Further comparisons and analyses are presented. [Received: 19 October 2021; Revised: 24 February 2022]
Keywords: humanitarian logistics; HL; foodbanks; natural disasters; optimisation; scenarios; stochastic.
A survey on network design problems: main variants
and resolution approaches
by Imen Mejri, Safa Bhar Layeb, Farah Zeghal
Abstract: Over the last decades, network design problems (NDPs) have been
one of the most investigated combinatorial optimisation problems that are still
catching the interest of both practitioners and researchers. In fact, NDPs pose
significant algorithmic challenges, as they are notoriously NP-hard, and arise in
several applications, mainly in logistics, telecommunication, and production
systems. Based on the literature published mainly between 1962 and 2021, this
paper provides a comprehensive taxonomy of NDPs and also identifies the
most investigated variants as well as their main fields of application. This
taxonomy highlights the diversity as well as the assets of this core class of
operations research problems. Moreover, the main mathematical formulations
and solution methods are reported. Finally, directions for future research on
NDPs are derived.
Keywords: network design problems; NDPs; literature review; survey;
An optimal supplier selection method for uncertain sustainable supply chains
by Qiurui Liu, He Huang, Ziqiang Zeng, Lin Chen, Junren Ming
Abstract: This paper considers a sustainable supplier selection problem with uncertainty faced by a transportation authority. The buyer tends to choose the supplier who can maximise its sustainable objectives including economic, energy, and quality aspects. We study the changes of design and quality requirements, as well as the interactions of the variables in the public transport production industry, affect the supplier selection decision making. The multi-objective particle swarm optimisation (MOPSO) solution method is employed to solve the sustainable supplier selection problem under uncertainty. Based on the computational results, the proposed model can help the managers to reduce the supply chain risk of quality uncertainty and design uncertainty. Theoretically, we provide an initial model that incorporates sustainability into supplier selection for transportation products, taking into account design uncertainty and environmental dimension. Practically, we measure the impact of design indicator on procurement from the perspectives of operators and users. It can be beneficial to the application and the integration of sustainable supply chain management. [Received: 25 October 2021; Accepted: 24 February 2022]
Keywords: sustainable supply chain; supplier selection; performance optimisation; decision-making model.
Data-driven imitation learning-based approach for order size determination in supply chains
by Dony S. Kurian, V. Madhusudanan Pillai, J. Gautham, Akash Raut
Abstract: Past studies have attempted to formulate the order decision-making behaviour of humans for inventory replenishment in dynamic stock management environments. This paper investigates whether a data-driven approach like machine learning can imitate the order size decisions of humans and consequently enhance supply chain performances. Accordingly, this paper proposes a supervised machine learning-based order size determination approach. The proposed approach is initially executed using the order decision data collected from a simulated stock management environment similar to the
Keywords: supply chain; order size determination; machine learning; behavioural experiments; LightGBM; imitation learning; beer game.
A survey on network design problems: main variants and resolution approaches
by Imen MEJRI, SAFA BHAR LAYEB, Farah ZEGHAL
Abstract: Over the last decades, network design problems (NDPs) have been one of the most investigated combinatorial optimisation problems that are still catching the interest of both practitioners and researchers. In fact, NDPs pose significant algorithmic challenges, as they are notoriously NP-hard, and arise in several applications, mainly in logistics, telecommunication, and production systems. Based on the literature published mainly between 1962 and 2021, this paper provides a comprehensive taxonomy of NDPs and also identifies the most investigated variants as well as their main fields of application. This taxonomy highlights the diversity as well as the assets of this core class of operations research problems. Moreover, the main mathematical formulations and solution methods are reported. Finally, directions for future research on NDPs are derived. [Received: 14 March 2021; Accepted: 23 January 2022]
Keywords: network design problems; NDPs; literature review; survey; combinatorial optimisation.
Risk-Averse Joint Facility Location-Inventory Optimization for Green Closed-Loop Supply Chain Network Design under Demand Uncertainty
by Ying Xu, Xiao Zhao, Pengcheng Dong, Guodong YU
Abstract: This paper considers a joint facility location-inventory optimisation for green closed-loop supply chain network design under demand uncertainty. Under the uncoordinated inventory policy, we propose a chance-constrained risk-averse bi-objective 0
Keywords: green closed-loop supply chain; facility location; inventory; risk-averse; chance constraint; distributionally robust optimisation.
A new framework for balancing and performance evaluation in stochastic assembly line using queueing networks
by MEHMET PINARBA?I, Mustafa Yüzük?rm?z?
Abstract: Real world assembly lines have a characterisation of variability in arrival, service and departure processes. Modelling these variabilities and their interactions, and the optimisation of a line have not been achieved yet. The purpose of this research is to provide an analytical solution framework for finding the best combinations of task assignment under variability. A queueing-based decomposition model that considers all variations sources has been proposed for the performance evaluation of a stochastic assembly line. A closed, nonlinear constraint programming model has been developed. Mathematical relations from the variability sources are established to measure the overall system performance. Numerical experiments which are conducted on several numerical examples demonstrate that the approach is a viable and an effective solution method. The results also indicate that changes in the coefficient of variance of either the service or arrival process, alter both the task assignment combinations, station workloads and line performance. [Received: 10 July 2021; Accepted: 19 January 2022]
Keywords: stochastic assembly line balancing; variability; queueing network; constraint programming; decomposition; simulation.
Searching for the Best Profit-Sharing Allocation in Multi-Echelon Supply Chain
by Hop Nguyen
Abstract: In this paper, we propose coordination procedures for a multi-echelon supply chain in which the appropriate profit-sharing rate is allocated for each supply chain member. The search process is first developed to maximise the total compromised profit of a two-member supply chain. From the achieved profit-sharing rate, the best ordering quantity is also determined. Then, a cascading procedure is also proposed for searching the best profit-sharing ratios for each member in the multi-echelon supply chain. Our proposed procedures are validated by comparing it with the fixed profit-sharing scheme. We have also investigated different scenarios to test the effect of demand variations on total cost at different profit-sharing rates. The obtained results are promising. [Received: 27 October 2020; Accepted: 22 January 2022]
Keywords: supply chain coordination; profit sharing; multi-echelon supply chain.
Robust Estimation of the Process Dispersion for Standard Deviation Control Charts
by Shih-Chou Kao
Abstract: The detection ability of control charts varies with the robustness of estimators against contamination. The aim of this current study is to develop six types of estimators based on the scale A method with distributed weight functions and compare the performance of various dispersion control charts based on these functions under normal and contaminated normal environments. The values of their mean squared error are compared to those of existing estimators in diffuse and localised disturbances. The process-monitoring abilities of phase II control charts using phase I contaminated estimators are assessed using disturbances and process shifts. The estimator with the logistic distributed weight function performs the best against disturbances, with its average run lengths being closer to those in uncontaminated cases compared to other estimators. [Submitted: 15 December 2019; Accepted 21 February 2022]
Keywords: average run length; ARL; mean squared error; MSE; scale A estimator; trimming; weight function.
Layout optimization of fishbone robotic mobile fulfillment system
by Yanyan Wang, Rongjun Man, Wanmeng Zhao
Abstract: Robotic mobile fulfilment system (RMFS) heavily influences all traditional scheduling problems when operating a warehouse. Rack layout affects the efficiency of inbound and outbound and the utilisation ratio of storage. This paper focuses on analysing the compatibility between fishbone storage layout and RMFS and its equipment kinetic characteristics, such as movement velocity and acceleration. By building the equipment kinetic functions and subsequently simulating various fishbone storage layout solutions features by length-to-width ratio, storage volume, and rack size, this research analyses the relationship between inbound/outbound efficiency and warehouse space utilisation. The applicability range of fishbone rack layout is obtained by comparing conventional layout with different rack size. Meanwhile, energy consumption is of great significance to reduce warehousing operating costs and improve operational efficiency. Therefore, the impacts on inbound/outbound efficiency and energy consumption from velocity and acceleration are investigated. Results show that optimal velocity ranges between 1.5 m/s and 2 m/s and the optimal acceleration ranges between 0.2 m/s2 and 0.25 m/s2. Too high acceleration or velocity is easy to cause congestion and deadlock, which is not easy to schedule. Overall, this research provides decision support for parts-to-picker system design.
Keywords: robotic mobile fulfilment system; RMFS; fishbone layout; layout optimisation.
Effects of trade credit insurance on remanufacturing decisions under carbon tax and emissions abatement
by Junfei Ding, Weida Chen
Abstract: This study examines the impacts of trade credit insurance on the optimal decisions of the firm that remanufactures used products and implements emissions abatement strategy under carbon tax policy. In the presence of revenue loss risks generated by uncertain factors in the trading process with channel partners, a remanufacturing production decision-making model without trade credit insurance is firstly proposed as a benchmark, and then the trade credit insurance is integrated into the model to alleviate risk. Subsequently, the optimal decisions for the two models are derived and the optimal emissions abatement rates for different objectives are characterised. Through analysis and numerical examples, the results show that the firm has an incentive to increase remanufacturing quantity and is better off with the use of trade credit insurance, regardless of whether the firm conducts emissions abatement strategy. The emissions abatement strategy is unable to maximise the production quantity, the insurance coverage quantity and the firms expected profit simultaneously. Additionally, although a high carbon tax decreases the firms profit, it motivates the firm to direct increasing efforts toward reducing emissions. [Submitted: 2 December 2020; Accepted: 20 September 2021]
Keywords: decision making; trade credit insurance; emissions abatement; remanufacturing; insurance premium rate.
Optimizing Green Vehicle Routing Problem-A Real Case Study
by Dalila Tayachi, Cheima Jendoubi
Abstract: The optimisation of distribution activities in the logistics scheme of various companies, long time based on economic objectives, is widening today to integrate environmental concerns. This paper addresses the fuel consumption minimisation problem for one variant of the green VRP which is the VRP with fuel consumption rate (FCVRP) and considers load and distance as two main factors affecting fuel consumption. The problem is classified as NP-hard, hence, we propose to solve it by an iterated local search meta-heuristic (ILSFC-SP) starting with a heuristic approach that is based on mathematical programming and generates solutions by CPLEX. In order to test its performance, ILSFC-SP was first applied on benchmark instances to minimise fuel consumption as well as travelled distance and compared with the literature where it proved its efficacy, then, it was applied to a real-world application in Tunisia where it suggested operational solutions reducing considerably the fuel costs. [Submitted: 28 June 2019; Accepted: 17 April 2022]
Keywords: fuel consumption; green vehicle routing problem; iterated local search; logistics; set-partitioning problem.
Coordination Strategies of Dual Channel Closed-loop Supply Chain Considering Demand Disruptions
by Di Wu, Peng Li, Juhong Chen, Hao Wang
Abstract: From the perspective of emergency management, it is of great practical significance to study the effect of demand disruptions on the decisions of dual channel closed-loop supply chain. Firstly, based on Stackelberg game theory, this paper constructs and solves the game model of dual channel closed-loop supply chain in centralised and decentralised decision modes, and analyses the effect of positive and negative demand disruptions on the optimal decision and profit of enterprises. Secondly, the construction of revenue-cost sharing contract realises the coordination between online and offline channels. Finally, a numerical example is used to further explore the effects of the factors on the equilibrium solution. The results show that: 1) when the degree of demand disruptions is small, the decision has certain robustness; 2) when demand has a negative disruption, the manufacturer will consider helping the retailer to reduce the loss on the premise of giving priority to reducing its own profit loss. Such behaviour is a typical
Keywords: demand disruptions; dual channel closed-loop supply chain; recovery rate; pricing strategies; coordination strategies.
Scenario-based stochastic shelter location-allocation problem with vulnerabilities for disaster relief network design
by Sweety Hansuwa, Usha Mohan, Viswanath Kumar Ganesan
Abstract: We formulate the shelter location-allocation problem considering the vulnerability of the demand locations and their network connectivities with the shelter locations for disaster management's preparedness and response phase. We propose a scenario-based stochastic model that assigns the set of candidate locations evaluating operational, budgetary limitations, and service level expectations. The solution presents an evacuee-allocation plan considering the best collection of less vulnerable network connectivities between the demand areas and the shelter locations. We present a linear relaxation heuristic and compare the heuristic performance with the scenario-based formulation solved using CPLEX 12.8 optimisation solver for various problem sizes. We finally apply and solve the problem using real-life case data obtained during the major flooding event in and around the Chennai Metropolitan Development Area during 2015 to present our model's applicability and emergency response requirements. [Submitted: 12 November 2020; Accepted: 19 April 2021]
Keywords: disaster management; shelter location-allocation; stochastic programming; linear relaxation heuristic.
An empirical analysis of the effect of customising project management tools and techniques on industrial SMEs' project success
by Eduardo García-Escribano, Adolfo López-Paredes, Javier Pajares
Abstract: Project managers have access to many tools and techniques to plan, monitor, and control their projects. However, not all of these project management tools and techniques (PMTT) are suited to the management of projects in all contexts and they may need to be customised or adjusted from the standard methodologies. The paper presents a comprehensive study with a duration of almost three years that used several research methods to answer the research questions posed. The study was made in 35 small and medium enterprises (SMEs), involving 94 projects in total and 54 project managers, focused on the manufacturing, healthcare, and telecommunications sectors. Although the results cannot be generalised, it is an interesting contribution relating to the tailoring of PMTT in SMEs and its correlation with a set of key performance indicators (KPIs) that measure project management performance. [Submitted: 22 February 2021; Accepted: 9 May 2021]
Keywords: empirical analysis; project management tools and techniques; PMTT; project success; project management standard methodologies; project monitoring; industrial SMEs; key performance indicators; KPIs; small and medium enterprises; SMEs.
Remanufacturing with material restrictions in monopoly and duopoly
by Tao Zhou, Kai Li, Shan-Lin Yang
Abstract: In this paper, we study firms' pricing and competitive strategies. We discuss a monopolistic scenario with an original supplier (OS) and a duopolistic scenario with an additional independent supplier (IS). Moreover, we investigate the effects of manufacturing cost, remanufacturing cost, customer discount factor, acquisition rate and the entry of a competitor on OS's strategies. Our results show that, in monopoly, the OS's remanufacturing possibility does not always increase in customer discount factor. Moreover, a lower manufacturing cost promotes complementary relationships between new and remanufactured products. In duopoly, a lower manufacturing cost reduces the remanufacturing possibility of the IS. Furthermore, raising the price of a remanufactured product may not reduce the consumer demand. The proposed model can be applied to many industries where the managers have the full awareness of extended producer responsibility, and they are willing to engage in the project related to remanufacturing. [Submitted: 2 January 2020; Accepted: 6 June 2021]
Keywords: remanufacturing; material restrictions; monopoly; duopoly; pricing.
An efficient mat-heuristic algorithm for the dynamic disassembly assembly routing problem with returns
by Sana Frifita, Hasan Murat Afsar, Faicel Hnaien
Abstract: We study a static and dynamic disassembly assembly routing problem with returns (2D-ARP-R). The problem presents the case where a set of disassembled components and raw materials are converted into a final product. By regrouping production and routing decisions, it is possible to synchronise different activities (assembly, disassembly, inventory management, and vehicle routing) and build a global optimal solution. A mixed integer linear programming (MILP) is presented to solve this new variant. A mat-heuristic based on integer programming and variable neighborhood search algorithm (VNS) is also developed to solve the larger size instances. Numerical results show that the mat-heuristic approach improves the upper bounds obtained by CPLEX in a much shorter time, in most cases. We also evaluate the benefits of coordination of the production and routing decisions within the same optimisation model. This benefit can reach up to 117.38% compared to the hierarchical approach. [Submitted: 4 April 2020; Accepted: 27 June 2021]
Keywords: supply chain management; assembly routing problem; ARP; disassembly problem; returns; mat-heuristic.
An improved AHP approach to select appropriate location sites for infectious medical waste disposal companies
by Hela Moalla Frikha, Ahmed Frikha
Abstract: Nowadays, infectious healthcare waste management has become a challenging task for the municipal authorities especially in developing countries including Tunisia, which considers this concern as one of the environmental priorities. Since these wastes have resistant impacts on public health and the deleterious effects on the environment, government authorities have deployed efforts to improve healthcare waste management. Locating infectious healthcare disposal firms is a sophisticated multi-criteria decision-making problem, which requires a compromise solution chosen according to conflicting criteria. This paper addresses the use of a modified analytic hierarchy process approach to select objectively the best sites for installing infectious healthcare waste disposal firms in Tunisia. A number of criteria and their sub-criteria are considered, several locations are evaluated, and the most appropriate ones are selected. Moreover, using expert choice software, sensitivity analysis is performed to show how sensitive the results are to the removal of one or more criteria. [Submitted: 21 January 2021; Accepted: 27 June 2021]
Keywords: decision analysis; multiple criteria decision aid; waste disposal firm; infectious healthcare waste management; location problem; analytic hierarchy process.