Article
Management
G. Van der Heide, K. J. Roodbergen, N. D. Van Foreest
Summary: Library organizations in the Netherlands are increasingly interested in using low-cost depots for storage and demand fulfillment. Two preferred methods for fulfilling requests are compared - cross docking and delayed shipments. The study derives optimal policies for different systems and reveals insights on the effectiveness of these methods in various situations.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Yuqi Wei, Min Yang, Jingxian Chen, Liang Liang, Tao Ding
Summary: This study proposes a lateral transshipment policy that considers both replenishment and recycling, models the inventory problem as stochastic dynamic programming, applies two dynamic programming methods to deal with the curse of dimensionality, and tests the proposed inventory policies using random demand samples. The results show that both policies are efficient in improving profitability and reducing waste.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Management
Leopoldo E. Cardenas-Barron, Rafael A. Melo
Summary: This study focuses on an NP-hard selective and periodic inventory routing problem (SPIRP) in a waste vegetable oil collection environment, proposing a MIP-based heuristic approach that proves to be fast and effective in improving existing best results.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Computer Science, Interdisciplinary Applications
Mina Dehghani Jeshvaghani, Maghsoud Amiri, Kaveh Khalili-Damghani, Laya Olfat
Summary: This paper addresses the production-inventory-routing problem (PIRP) in Fast-Moving Consumer Goods (FMCG) supply chains, considering multi-products, multi-periods, and the reverse flow of defective products in a four-echelon system. The consolidation of cross-dock tasks is also taken into account. Robust possibilistic programming and possibilistic chance-constrained programming are used to model demand uncertainty. Meta-Heuristics algorithms are applied to solve the deterministic equivalence of the models. The results demonstrate the effectiveness and robustness of the proposed models and solution procedures in real-life FMCG supply chains.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Economics
Muge Acar, Onur Kaya
Summary: In case of disaster, NGOs need to make decisions on how to allocate budget for pre and post-disaster usage. This is because using all the budget before the disaster can lead to high holding costs if there is no disaster in the long term, while reserving all the budget for use after the disaster may result in higher costs or unmet demand. Our study analyzes the dynamic stocking decisions of NGOs under budget constraints using stochastic dynamic programming models.
SOCIO-ECONOMIC PLANNING SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Vincent F. Yu, Nabila Yuraisyah Salsabila, Nurhadi Siswanto, Po-Hsun Kuo
Summary: The research proposes a joint optimization model for managing spare parts inventory and planned maintenance to balance inventory cost and spare parts availability. The study shows that the independent policy results in lower cost than the aggregate policy, and the proposed Genetic Algorithm performs efficiently for large-scale problems.
APPLIED SOFT COMPUTING
(2022)
Article
Engineering, Manufacturing
Mila Nambiar, David Simchi-Levi, He Wang
Summary: This study investigates a multi-period inventory allocation problem with the impact of demand learning on decision making in a two-period setting. The research shows that demand learning incentivizes decision makers to withhold inventory at the warehouse rather than allocating it early on.
PRODUCTION AND OPERATIONS MANAGEMENT
(2021)
Article
Computer Science, Interdisciplinary Applications
Leopoldo E. Cardenas-Barron, Rafael A. Melo, Marcio C. Santos
Summary: This paper explores the multi-item inventory lot-sizing problem with supplier selection, proving its NP-hardness and proposing a facility location extended formulation based on cost structure, with new valid inequalities. Additionally, a MIP heuristic is introduced to effectively reduce the size of the formulation and improve solving efficiency. Results show the proposed heuristic outperforms existing ones and can significantly reduce the number of instances solved to optimality within the time limit.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Management
Yi Wang, Sheng Hao Zhang
Summary: This study examines the impact of partner selection on the value of information sharing in a distribution system. The findings suggest that partnering with the high priority retailer is more effective, and a selective-information sharing system serves as an effective pilot run to full-information sharing.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Management
Saif Benjaafar, Daniel Jiang, Xiang Li, Xiaobo Li
Summary: The paper explores an optimal policy for systems with a general network structure in the context of on-demand rental services. It demonstrates that the optimal policy can be described in terms of a specific region in the state space and proposes a provably convergent approximate dynamic programming algorithm to handle high-dimensional problems.
MANAGEMENT SCIENCE
(2022)
Article
Management
Burak Buke, Mesut Sayin, Fehmi Tanrisever
Summary: This paper proposes a new multi-level iterative heuristic to clear the Turkish day-ahead electricity market auctions. It achieves an average optimality gap less than 0.09% and an average solution time of just 14 seconds, outperforming a commercial solver that takes an average of 18 minutes to find the optimal solution.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2023)
Article
Engineering, Industrial
Serhat Saylam, Melih Celik, Haldun Sural
Summary: This paper investigates the order picker routing problem in a dynamic and synchronised zoning environment, aiming to minimize the maximum time of completing picking activities in any zone. The use of a min-max type objective helps balance the workload of order pickers more effectively.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Meisam Pour-Massahian-Tafti, Matthieu Godichaud, Lionel Amodeo
Summary: This paper addresses the problem of disassembly lot-sizing for the single-product type, proposing three new MIP formulations and investigating two efficient heuristics for real-case applications. The research highlights the relevance of disposal decisions in disassembly lot-sizing models for saving inventory costs.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Management
Yuksel Asli Sari, M. Kumral
Summary: The complexity of sublevel stope layout problem is shown to be a special case of the independent set problem, which is NP-hard. A new approach based on dynamic programming is proposed to efficiently solve the problem by memoizing subproblems and introducing a greedy heuristic method to further optimize solution time and memory usage. Results from case studies demonstrate the effectiveness of the approach in generating fast and accurate stope layout plans.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2021)
Article
Engineering, Multidisciplinary
H. Abdullah Ali Ahmadini, Umar Muhammad Modibbo, Ali Akbar Shaikh, Irfan Ali
Summary: In this study, a multi-objective inventory model with green investment is proposed to address the increasing pressure to conserve the environment from global warming. The model is formulated as a multi-objective fractional programming problem with various objectives and constraints, aiming to provide useful suggestions to decision-makers in the manufacturing sectors.
ALEXANDRIA ENGINEERING JOURNAL
(2021)
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)