Article
Engineering, Chemical
Congqin Ge, Lifeng Zhang, Zhihong Yuan
Summary: This paper proposes a hybrid stochastic and distributionally robust optimization approach to tackle uncertainty and disruptions in the closed-loop supply chain network. By customizing an algorithm, large-scale mixed integer linear programming problems can be solved efficiently. Computational experiments demonstrate the advantages of this approach in terms of costs and variances.
Article
Computer Science, Interdisciplinary Applications
Alireza Goli, Erfan Babaee Tirkolaee
Summary: Product portfolio design plays a crucial role in the financial and physical flows of supply chains, especially for dairy products. This study proposes a closed-loop supply chain network for dairy products to maximize net cash flow and shareholder payments. The accelerated Benders decomposition algorithm and three multi-objective optimization methods are used to address the complexity and bi-objectiveness of the model, respectively. A real case study in Iran shows significant improvements in net cash flow and shareholder payments compared to the current situation, while reducing CPU time by 10.8%.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Chang Liu, Ying Ji, Xinqi Li
Summary: This paper incorporates flexible facility capacity and government subsidy factors into the consideration of the design of a closed-loop supply chain network. It constructs a multi-objective multi-period multi-product mixed integer linear programming model with fixed and flexible facility capacity, and applies the robust optimization method to deal with the uncertain environment. The paper also proposes a solution algorithm that combines the augmented epsilon-constraint method and a three-stage method for efficient problem solving. Through numerical cases, the paper verifies the effectiveness of a flexible supply strategy in managing economic and environmental costs, and analyzes the potential limitations of the government subsidy strategy.
Article
Green & Sustainable Science & Technology
Abbas Al-Refaie, Yasmeen Jarrar, Natalija Lepkova
Summary: The design and implementation of closed loop supply chains are crucial for the economic and environmental sustainability of businesses, yet they also face challenges of complexity. This study applied a multistage stochastic model on durable products, considering uncertainty in demand, return rate, and return quality, providing valuable analysis for decision-makers in supply chain planning.
Article
Engineering, Industrial
Abdolmajid Yolmeh, Ullah Saif
Summary: Recent research has shown the interdependence between closed-loop supply chain network design and line balancing decisions, leading to the development of a mixed integer non-linear programming model and an enhanced decomposition approach to solve the problem. Computational results demonstrate the efficiency of the enhanced decomposition approach compared to existing methods, highlighting the importance of integrating supply chain network design and line balancing decisions.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Engineering, Industrial
Xuhui Chen, Yong He, Li Zhou
Summary: The increase in Chinese residents' income has led to a significant rise in the purchase of household durable metal products (HDMPs), including automobiles, appliances, and electronics. This study explores the energy efficiency potential of the closed-loop supply chain (CLSC) for the HDMP industry in China using dynamic material flow analysis and life cycle assessment. The findings indicate that the demand for appliances, electronics, and electric cars will peak in certain years, and recycling and remanufacturing processes can greatly reduce energy consumption compared to primary metal production.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Meysam Borajee, Reza Tavakkoli-Moghaddam, Seyed-Houman Madani-Saatchi
Summary: This paper develops a multi-period, multi-brand stochastic mixed-integer linear programming (MILP) model for the closed-loop supply chain (CLSC) network design. Uncertainties in new and secondhand product demand are considered using a chance-constraint optimization (CCO) approach. The accelerated Benders decomposition (BD) algorithm is applied to solve the proposed model. Test problems are used to compare the accelerated BD with the conventional BD algorithm, and the results are analyzed and future research suggestions are provided.
COMPUTERS & OPERATIONS RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Mitra Moubed, Yasamin Boroumandzad, Ali Nadizadeh
Summary: The study focuses on optimizing decisions for deteriorating products in a closed-loop supply chain. Through simulations under different strategy groups, it is found that better warehousing conditions and more frequent collections result in the best performance indicators.
SIMULATION MODELLING PRACTICE AND THEORY
(2021)
Article
Business
Ata Allah Taleizadeh, Mohammad Sadegh Moshtagh, Behdin Vahedi-Nouri, Biswajit Sarkar
Summary: If remanufactured and fresh products are available in the market at the same price and quality, retailers face difficulties in selling them simultaneously. Despite similar price and quality, consumers differentiate between them. Remanufactured products are a result of closed-loop supply chains, which focus on environmental and social issues. A mathematical model is proposed to tackle the imperfect production system in a multi-cycle closed-loop supply chain, where reworking occurs within the same cycle. The model considers the acceptance quality level and employs algorithms to achieve local and global optima. Results show that retailers can effectively manage the closed-loop supply chain for maximum profit.
JOURNAL OF RETAILING AND CONSUMER SERVICES
(2023)
Article
Computer Science, Interdisciplinary Applications
Benrong Zheng, Liang Jin
Summary: This study examines the issue of remanufacturing patent licensing in secondary markets and compares two relicensing schemes. The results show that the OEM earns higher profits when licensing a third-party for remanufacturing, and consumers benefit more in this model. Additionally, when consumers have a high willingness-to-pay for remanufactured products, the OEM licensing the retailer for remanufacturing performs better.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Operations Research & Management Science
Chao Zhao, Daoping Wang, Amjad Younas, Boqing Zhang
Summary: This paper investigates the coordination issue in a closed-loop supply chain under remanufactured product quality control. It is found that the closed-loop supply chain cannot achieve coordination, and the introduction of a wholesale price and quality cost-sharing contract is proven to be an effective solution.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Engineering, Manufacturing
Dongmin Son, Songi Kim, Bongju Jeong
Summary: This study proposes a new supply chain model that combines the advantages of both AM and CM systems to effectively improve the sustainability of the entire lifecycle. Experimental analysis demonstrates that the AM hub and PC model can enhance production efficiency, with the pre-manufacturing stage having the greatest impact on the cost sustainability index.
ADDITIVE MANUFACTURING
(2021)
Article
Management
Nils Boysen, Simon Emde, Stefan Schwerdfeger
Summary: Crowdshipping transfers the basic idea of the sharing economy to retailers' last-mile deliveries, connecting private drivers' transport capacities with retailers' home delivery needs. To ensure promised delivery services, retailers establish crowdshipping platforms rewarding employees for crowdshipping online orders on their way back from work. An efficient exact solution based on Benders decomposition is presented to maximize matched shipments while considering employees' earnings, solving real-world instances before the end of a work shift.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Environmental Sciences
Leyla Ozgur Polat, Askiner Gungor
Summary: This study proposes a mixed integer programming model for decision-makers to manage their activities on the WEEE closed-loop supply chain network, integrating product returns with different quality and damage levels. The results indicate that the capacity balance among stores, producers, and recovery centers is vital to make the network profitable and sustainable.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Article
Mathematics
Lang Liu, Yutao Pu, Zhenwei Liu, Junjie Liu
Summary: This paper explores the impact of consumer purchase regret on dynamic closed-loop supply chains (CLSCs) under discrete-time conditions. It introduces the factor of purchase regret psychology into the traditional Bass model and constructs a CLSC model led by the manufacturer and followed by the retailer and recycler. The optimal control theory is used to obtain the optimal decision sequence for each participant in the CLSC. The analysis shows that purchase regret affects the pricing strategy, sales, and profits of manufacturers and retailers, but not the profits of recyclers.
Article
Management
Mohammad Jeihoonian, Masoumeh Kazemi Zanjani, Michel Gendreau
Summary: Motivated by the recovery of modular-structured products, this study proposes a flexible design model for a reverse supply chain (RSC) that considers the uncertain behavior of product returns. The model is decomposed into smaller scenario cluster submodels and coordinated using a Lagrangian-progressive hedging-based method. Computational results based on a realistic case demonstrate the superiority of the proposed model and the efficiency of the solution approach.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2022)
Article
Engineering, Industrial
Adrien Rimele, Michel Gamache, Michel Gendreau, Philippe Grangier, Louis-Martin Rousseau
Summary: RMFS is a type of automated warehouse system recently deployed in e-commerce, consisting of a fleet of small robots tasked with retrieving and storing items in the warehouse. Due to the nature of the e-commerce market and the flexibility of RMFS, there are opportunities to improve warehouse productivity by optimizing operational decisions. Researchers have proposed a mathematical framework to model operational decisions in RMFS as a stochastic dynamic program, aiming to formalize optimization opportunities for developing more advanced methods in a well-defined environment.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Management
Xiangyi Zhang, Lu Chen, Michel Gendreau, Andre Langevin
Summary: In this study, a branch-and-cut algorithm is developed for the vehicle routing problem with two-dimensional loading constraints. The algorithm is shown to be competitive through experimental results, and extensive computational analysis is conducted to investigate the impact of different factors on the algorithm.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Review
Management
Seyed Sina Mohri, Mehrdad Mohammadi, Michel Gendreau, Amir Pirayesh, Ali Ghasemaghaei, Vahid Salehi
Summary: This paper provides a comprehensive review of hazardous material transportation from an Operational Research perspective, with a focus on hazmat routing, routing-scheduling, and network design problems. The paper reviews the assumptions, objectives, constraints, and solutions of the models, along with case studies. It also highlights the challenges and features of designing models for different transportation modes, and identifies research gaps and future directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Engineering, Industrial
Hoora Katoozian, Masoumeh Kazemi Zanjani
Summary: This study proposes a mixed-integer programming model to obtain the optimal configuration of a supply network for highly-customized and modular-structured products. The results show that the configuration of the supply network depends on the demand as well as market conditions, production capacity, flexibility of processes, and cost structure of manufacturers.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2022)
Article
Engineering, Industrial
Shayan Tavakoli Kafiabad, Masoumeh Kazemi Zanjani, Mustapha Nourelfath
Summary: This study proposes a two-stage robust optimization model for collaborative design and planning of maintenance networks under demand uncertainty, aiming to minimize the cost of late deliveries. By sharing resources among different maintenance facilities, delays in the delivery of repaired devices can be reduced effectively.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2022)
Review
Management
Vinicius N. Motta, Miguel F. Anjos, Michel Gendreau
Summary: This survey presents a review of optimization approaches for the integration of demand response in power systems planning and highlights important future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Jonathan De La Vega, Michel Gendreau, Reinaldo Morabito, Pedro Munari, Fernando Ordonez
Summary: This paper tackles the vehicle routing problem with time windows and stochastic demands (VRPTWSD). It presents a two-stage stochastic program with recourse for modeling the problem, where routes are planned in the first stage and executed in the second stage. The paper proposes an Integer L-shaped algorithm that considers different recourse actions such as reactive trips, preventive trips, and additional actions to handle violated time windows. Experimental results using benchmark instances demonstrate the effectiveness of the proposed algorithm, particularly when using the fixed rule-based policy.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Management
Alexandre M. Florio, Michel Gendreau, Richard F. Hartl, Stefan Minner, Thibaut Vidal
Summary: This paper examines the stochastic variant of the Vehicle Routing Problem (VRP) called VRPSD, where demands are only revealed upon vehicle arrival at each customer. The paper summarizes recent progress in VRPSD research and introduces two major contributions: a branch-price-and-cut algorithm for optimal restocking and a demand model for correlated customer demands. Computational results demonstrate the effectiveness of the new algorithm and the potential cost savings of over 10% when considering demand correlation.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Management
Behnam Vahdani, Mehrdad Mohammadi, Simon Thevenin, Michel Gendreau, Alexandre Dolgui, Patrick Meyer
Summary: This paper proposes a new model for vaccine distribution, addressing various concerns such as prioritizing age groups, fair distribution, multi-dose injection, and dynamic demand. The proposed solution approach, which includes a Benders decomposition algorithm, is faster and provides better-quality solutions compared to existing solvers. Numerical experiments on the vaccination campaign in France demonstrate the applicability and performance of the model.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Operations Research & Management Science
Tommaso Schettini, Michel Gendreau, Ola Jabali, Federico Malucelli
Summary: Metro lines are a crucial part of urban public transport in many cities, offering a greener and more efficient alternative to private transportation. However, these lines are often resource constrained, making it difficult to expand capacity. To make better use of existing resources, researchers and operators are exploring ways to adapt timetables to forecasted demand and limited vehicle capacities.
TRANSPORTATION SCIENCE
(2023)
Article
Management
Shayan Tavakoli Kafiabad, Masoumeh Kazemi Zanjani, Mustapha Nourelfath
Summary: This study proposes a multistage stochastic programming model for operations planning under independent random demand. A decomposition heuristic is developed to efficiently solve the problem by decomposing the model into submodels and coordinating them via a subgradient algorithm to obtain a high-quality feasible solution.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2023)
Article
Engineering, Industrial
Milad Ghorbani, Mustapha Nourelfath, Michel Gendreau
Summary: This study investigates selective maintenance for multi-component systems undergoing consecutive missions, using a two-stage stochastic programming approach to address uncertainties and enhance the likelihood of mission success.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Computer Science, Interdisciplinary Applications
Xiangyi Zhang, Lu Chen, Michel Gendreau, Andre Langevin
Summary: This study addresses a capacitated vehicle routing problem with two-dimensional loading constraints, presenting an exact branch-and-price algorithm and an approximate counterpart to solve the challenging combination of two NP-hard problems. By introducing a supervised learning model in the new column generation mechanism, the algorithm demonstrates significant improvements in efficiency in terms of CPU time and feasibility checker calls.
INFORMS JOURNAL ON COMPUTING
(2022)
Review
Management
Vinicius N. Motta, Miguel F. Anjos, Michel Gendreau
Summary: This survey presents a review of optimization approaches for the integration of demand response in power systems planning and highlights important future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Philipp Schulze, Armin Scholl, Rico Walter
Summary: This paper proposes an improved branch-and-bound algorithm, R-SALSA, for solving the simple assembly line balancing problem, which performs well in balancing workloads and providing initial solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Roshan Mahes, Michel Mandjes, Marko Boon, Peter Taylor
Summary: This paper discusses appointment scheduling and presents a phase-type-based approach to handle variations in service times. Numerical experiments with dynamic scheduling demonstrate the benefits of rescheduling.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Oleg S. Pianykh, Sebastian Perez, Chengzhao Richard Zhang
Summary: Efficient scheduling is crucial for optimizing resource allocation and system performance. This study focuses on critical utilization and efficient scheduling in discrete scheduling systems, and compares the results with classical queueing theory.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Review
Management
Hamed Jahani, Babak Abbasi, Jiuh-Biing Sheu, Walid Klibi
Summary: Supply chain network design is a large and growing area of research. This study comprehensively surveys and analyzes articles published from 2008 to 2021 to detect and report financial perspectives in SCND models. The study also identifies research gaps and offers future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Patrick Healy, Nicolas Jozefowiez, Pierre Laroche, Franc Marchetti, Sebastien Martin, Zsuzsanna Roka
Summary: The Connected Max-k-Cut Problem is an extension of the well-known Max-Cut Problem, where the objective is to partition a graph into k connected subgraphs by maximizing the cost of inter-partition edges. The researchers propose a new integer linear program and a branch-and-cut algorithm for this problem, and also use graph isomorphism to structure the instances and facilitate their resolution. Extensive computational experiments show that, if k > 2, their approach outperforms existing algorithms in terms of quality.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Victor J. Espana, Juan Aparicio, Xavier Barber, Miriam Esteve
Summary: This paper introduces a new methodology based on the machine learning technique MARS for estimating production functions that satisfy classical production theory axioms. The new approach overcomes the overfitting problem of DEA through generalized cross-validation and demonstrates better performance in reducing mean squared error and bias compared to DEA and C2NLS methods.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Stefano Nasini, Rabia Nessah
Summary: In this paper, the authors investigate the impact of time flexibility in job scheduling, showing that it can significantly affect operators' ability to solve the problem efficiently. They propose a new methodology based on convex quadratic programming approaches that allows for optimal solutions in large-scale instances.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Zhiqiang Liao, Sheng Dai, Timo Kuosmanen
Summary: Nonparametric regression subject to convexity or concavity constraints is gaining popularity in various fields. The conventional convex regression method often suffers from overfitting and outliers. This paper proposes the convex support vector regression method to address these issues and demonstrates its advantages in prediction accuracy and robustness through numerical experiments.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Kuo-Hao Chang, Ying-Zheng Wu, Wen-Ray Su, Lee-Yaw Lin
Summary: The damage and destruction caused by earthquakes necessitates the evacuation of affected populations. Simulation models, such as the Stochastic Pedestrian Cell Transmission Model (SPCTM), can be utilized to enhance disaster and evacuation management. The analysis of SPCTM provides insights for government officials to formulate effective evacuation strategies.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Qinghua Wu, Mu He, Jin-Kao Hao, Yongliang Lu
Summary: This paper studies a variant of the orienteering problem known as the clustered orienteering problem. In this problem, customers are grouped into clusters and a profit is associated with each cluster, collected only when all customers in the cluster are served. The proposed evolutionary algorithm, incorporating a backbone-based crossover operator and a destroy-and-repair mutation operator, outperforms existing algorithms on benchmark instances and sets new records on some instances. It also demonstrates scalability on large instances and has shown superiority over three state-of-the-art COP algorithms. The algorithm is also successfully applied to a dynamic version of the COP considering stochastic travel time.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Bjorn Bokelmann, Stefan Lessmann
Summary: Estimating treatment effects is an important task for data analysts, and uplift models provide support for efficient allocation of treatments. However, evaluating uplift models is challenging due to variance issues. This paper theoretically analyzes the variance of uplift evaluation metrics, proposes variance reduction methods based on statistical adjustment, and demonstrates their benefits on simulated and real-world data.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Congzheng Liu, Wenqi Zhu
Summary: This paper proposes a feature-based non-parametric approach to minimizing the conditional value-at-risk in the newsvendor problem. The method is able to handle both linear and nonlinear profits without prior knowledge of the demand distribution. Results from numerical and real-life experiments demonstrate the robustness and effectiveness of the approach.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Laszlo Csato
Summary: This paper compares the performance of the eigenvalue method and the row geometric mean as two weighting procedures. Through numerical experiments, it is found that the priorities derived from the two eigenvectors in the eigenvalue method do not always agree, while the row geometric mean serves as a compromise between them.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Guowei Dou, Tsan-Ming Choi
Summary: This study investigates the impact of channel relationships between manufacturers on government policies and explores the effectiveness of positive incentives versus taxes in increasing social welfare. The findings suggest that competition may be more effective in improving sustainability and social welfare. Additionally, government incentives for green technology may not necessarily enhance sustainability.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
