Article
Engineering, Industrial
Daniel Y. Mo, Yue Wang, Danny C. K. Ho, K. H. Leung
Summary: Service parts management is crucial for generating high profits, but faces challenges. Redeploying excess inventories can reduce costs and improve efficiency.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Management
Nathalie Vanvuchelen, Kim De Boeck, Robert N. Boute
Summary: This study investigates how transshipment can improve service levels, equity, and inventory levels in Zambia's public pharmaceutical supply chain. The researchers use advanced deep reinforcement learning and heuristics to develop transshipment policies and compare their performance in resource-constrained and sufficient inventory scenarios. The findings provide policy insights for decision-makers in humanitarian health contexts.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
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
Nagihan Comez-Dolgan, Hilal Dag, Nilgun Fescioglu-Unver, Alper Sen
Summary: This study addresses the problem of assortment planning for a manufacturing firm with multiple plants. The company faces the challenge of allocating production capabilities efficiently among the plants in order to maximize profit. Transshipment and substitution are taken into account to ensure customer satisfaction. The study provides insights into the properties of optimal assortments and proposes algorithms for approximate assortment planning.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Management
Nicky D. Van Foreest, Onur A. Kilic
Summary: In this research note, it is shown that applying Breiman's work from 1964 on optimal stopping can lead to an elementary proof of the fact that (s, S) policies minimize the long-run average cost for periodic-review inventory control problems. The proof method is appealing as it only relies on basic concepts of renewal-reward processes, optimal stopping, dynamic programming, and root-finding. Furthermore, it provides an efficient algorithm for computing the optimal policy parameters. If Breiman's paper had received the attention it deserved, computational methods for (s, S)-policies could have been discovered about three decades earlier than the famous algorithm by Zheng and Federgruen (1991).
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Agriculture, Multidisciplinary
Parichehr Paam, Regina Berretta, Rodolfo Garcia-Flores, Sanjoy Kumar Paul
Summary: This study proposes a method to develop an efficient operation regime for warehouses in order to manage the food supply chain sustainably and profitably. By solving a multi-period, multi-product, multi-warehouse inventory control optimization problem, the study reduces costs and product deterioration, and analyzes the impact of variations in demand and supply on solution times.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Computer Science, Interdisciplinary Applications
Xiaofeng Xu, Zhifei Wei
Summary: This study builds a multi-objective mathematical model for the dynamic pickup and delivery problem with transshipsments and LIFO constraints (DPDPTL), aiming to minimize driving distance and maximize order satisfaction. The model considers the synchronization time of vehicle arrivals to obtain overlapping time windows for order transshipments. Additionally, an improved heuristic algorithm is proposed to address the LIFO constraints and improve solution quality.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Automation & Control Systems
Syeda Sakira Hassan, Simo Sarkka
Summary: This article proposes a novel computational method for solving nonlinear optimal control problems. The method uses Fourier-Hermite series to approximate the action-value function in dynamic programming and uses sigma-point methods to numerically compute the coefficients of the series. The method is proven to have quadratic convergence and its performance is tested experimentally.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Engineering, Industrial
Nagihan Comez-Dolgan, Lama Moussawi-Haidar, Mohamad Y. Jaber, Ecem Cephe
Summary: This study analyzes a joint assortment optimization problem for multiple locations of a firm with assortment capacity. It shows that the resulting problem is NP-complete and provides structural properties that simplify the search for the optimal solution. The study also examines the impact of transshipment and demand substitution in multi-location assortment planning.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2022)
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
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
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
Operations Research & Management Science
Wen Chen, Ying He
Summary: We study a multi-period inventory system with price-sensitive demand and uncertain supplier, and explore the advantage of delivery flexibility. By comparing our system with traditional systems numerically, we show that delivery flexibility can improve total profit and mitigate supply risk.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Computer Science, Information Systems
Yurong Guo, Quan Shi, Chiming Guo
Summary: This article focuses on the joint optimization of spare part management and spare part supply chain network optimization in multiple supply periods. A dynamic nonlinear programming model and an improved self-adaptive dynamic migrating particle swarm optimization algorithm are proposed to minimize the total cost.
Article
Automation & Control Systems
Derong Liu, Shan Xue, Bo Zhao, Biao Luo, Qinglai Wei
Summary: This article reviews the recent development of adaptive dynamic programming (ADP) with applications in control, highlighting efficient algorithms and future research directions. ADP is applied in optimization, game theory, and large-scale systems, showing great potential in the era of artificial intelligence.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Management
Dongmei Xue, Ruud H. Teunter, Stuart X. Zhu, Weihua Zhou
Summary: This paper examines a duopoly channel in the context of the smartphone industry, where a high-end firm sells its own brand at a high profit margin and a low-end firm sells its own brand at a low profit margin but can differentiate by remanufacturing high-end cores. The study analyzes how cost structure and customers' valuation influence the equilibrium strategies of both firms, including conditions for the low-end firm to engage in remanufacturing and how the high-end firm reacts to maintain its market share.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Management
Michiel A. J. Uit Het Broek, Ruud H. Teunter, Bram de Jonge, Jasper Veldman
Summary: This study investigates the value of condition-based load-sharing for two-unit systems with economic dependency, finding that substantial cost savings of up to 40% can be achieved compared to the optimal condition-based maintenance policy. The structure of the optimal policy is influenced by maintenance setup costs and penalties for not meeting production targets.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Management
Dennis Prak, Ruud Teunter, Mohamed Zied Babaic, John E. Boyland, Aris Syntetos
Summary: Existing methods for estimating parameters in inventory control lack guidance, with traditional MM and ML estimators proving to be less robust. We propose a new MM alternative that outperforms standard methods in accuracy and performance.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Management
Weijian Zhang, Xianliang Shi, Anqiang Huang, Guowei Hua, Ruud H. Teunter
Summary: Combating epidemics is a significant threat to humanity, and quick access to sufficient medical supplies is crucial. This study is the first to consider capital reserves in addition to physical stocks, and it reveals that increased demand uncertainty can lead to lower safety stock levels, making reliance on capital reserves a better option.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Fabio Neves-Moreira, Jasper Veldman, Ruud H. Teunter
Summary: Service operation vessels have become the dominant mode for maintaining offshore wind farms, but current repair kit problem approaches fail to account for all characteristics. Proposed mixed-integer programming models aim to determine and validate repair kits under different weather conditions to reduce turbine downtime and allow emergency resupplies. Valuable insights on repair kit composition and relevant business indicators for various scenarios are provided, emphasizing the importance of adapting repair kits based on weather forecasts and the potential for significant downtime reductions through emergency resupply allowances.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Engineering, Industrial
Michiel A. J. Uit Het Broek, Ruud H. Teunter, Bram de Jonge, Jasper Veldman
Summary: Condition-based maintenance and production policies play important roles in manufacturing industry as they can reduce costs and improve reliability by dynamically adjusting production rates and implementing maintenance. Integrating maintenance and production policies together can effectively lower failure risks and achieve higher cost savings.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Engineering, Industrial
Niels van der Laan, Ruud H. Teunter, Ward Romeijnders, Onur A. Kilic
Summary: This paper addresses the data-driven newsvendor problem under a service-level constraint. Existing approaches suffer from overfitting and fail to achieve the target service-level. To overcome this issue, the authors propose new data-driven approaches based on distributionally robust chance constrained optimization. Extensive experiments, including simulations and a real-life bikesharing system, demonstrate the effectiveness of the proposed methods.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2022)
Article
Management
T. A. Arno Kasper, Martin J. Land, Ruud H. Teunter
Summary: This study proposes a shift towards system state dispatching in the production control literature on high-variety manufacturing. The results show that FOCUS enables a big leap forward in production control performance, significantly reducing the number of orders delivered late and mean tardiness compared to state-of-the-art production control methods.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2023)
Article
Management
Luoyi Sun, Guowei Hua, T. C. E. Cheng, Ruud H. Teunter, Jingxin Dong, Yixiao Wang
Summary: Online sharing platforms have gained attention in various industries and have potential for the 3D printing industry. This paper explores the optimal pricing strategy for a 3DP capacity sharing platform and examines how usage level and printer heterogeneity impact consumers' choice between owning or renting. The study emphasizes the importance of technological progress in reducing printer prices to benefit the industry.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Management
Ruud H. Teunter, Stefan Kuipers
Summary: This study examines the optimal inventory control of two products with demand substitution. Using a simplified Economic Order Quantity model, the authors present new insights into the optimal ordering strategies for two substitute products and find that partial substitution is always achieved through one-way substitution rather than two-way substitution.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2022)
Article
Management
Yue Cai, Ruud H. Teunter, Bram de Jonge
Summary: Developments in sensor techniques enable continuous monitoring and better prediction of failures in operating systems, leading to improved maintenance decisions. This study presents a novel fully data-driven approach for condition-based maintenance, which sets the maintenance threshold purely based on past condition data and failures. Numerical results demonstrate the convergence of the data-driven approach to the optimal threshold.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Engineering, Industrial
T. A. Arno Kasper, Martin J. Land, Ruud H. Teunter
Summary: Reducing Work-In-Process (WIP) in manufacturing systems has advantages such as predictable throughput times and increased manageability. Various WIP control methods, including CONWIP and Kanban for repetitive manufacturing, and LUMS COR and POLCA for high-variety manufacturing, have been developed. By simultaneously considering release, authorization, and dispatching decisions, the non-hierarchical method DRACO outperforms traditional methods and improves overall manageability.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2023)
Article
Engineering, Manufacturing
Luoyi Sun, Guowei Hua, Ruud H. Teunter, T. C. E. Cheng, Zuo-Jun Max Shen
Summary: The rapid development of blockchain technology has prompted traditional centralized intermediaries to rethink their transaction models, especially in the peer-to-peer market. Token-based blockchain systems with cryptocurrency are gaining popularity, but little is known about how they compare to non-token-based systems. This study uses an analytical framework to determine the optimal strategies for both types of platforms and analyzes their properties and characteristics. The findings suggest that transitioning from non-token-based platforms to token-based platforms can increase social welfare, unless the non-token-based system has significantly higher prices. Additionally, the research finds that token-based platforms have higher matching probabilities and government interventions can improve social welfare by promoting fair consensus mechanisms and higher decentralization levels.
PRODUCTION AND OPERATIONS MANAGEMENT
(2023)
Article
Economics
Yixiao Wang, Eric Pels, Ruud H. Teunter, Luoyi Sun, Jianhong Wu
Summary: This study uses a game theoretic model to analyze the impact of infrastructure pricing regulation on various aspects, such as demand, social welfare, and investment in transport management. The study finds that product differentiation by transport operators and profit/welfare orientation of infrastructure operators significantly affect the sensitivity of transport mode to access charges. Additionally, numerical studies show that the introduction of HSR on-track competition and congested infrastructures have different effects on industry benefits and consumer surplus in European and Chinese markets.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2023)
Article
Management
Meng Wu, Stuart X. Zhu, Ruud H. Teunter
Summary: The research discusses the advantages of firms offering advance orders for new products, analyzing the trade-offs between these advantages and the revenue loss from selling at a discount in advance. The study also examines the question of whether firms should advertise the advance ordering opportunity for strategic consumers. Several structural insights into the optimal policy are provided, showing that the policy is driven by the proportion of strategic consumers and the discount level needed to encourage advance purchases.
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)