Article
Computer Science, Interdisciplinary Applications
Nan Zhang, Sen Tian, Jiatao Xu, Yingjun Deng, Kaiquan Cai
Summary: This paper proposes an integrated Economic manufacturing quantity (EMQ) model that combines the concepts of condition-based maintenance (CBM) and imperfect manufacturing process. The manufacturing process is modeled by binary state indicators and a homogeneous Gamma process. An integrated production and CBM policy is proposed to minimize the expected cost rate in the long-term. The problem is solved using a semi-Markov decision process framework and the successive-approximations method.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
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
Computer Science, Interdisciplinary Applications
Siqi Qiu, Xinguo Ming, Mohamed Sallak, Jialiang Lu
Summary: This study proposed a joint optimization of production and maintenance in make-to-order manufacturing systems by considering the influence of customer orders on the deterioration process of production machines and modeling different types of dependencies among production machines.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Engineering, Industrial
Yukun Wang, Xiaopeng Li, Junyan Chen, Yiliu Liu
Summary: This paper proposes a condition-based maintenance (CBM) optimization approach for complex systems. The decision rule at the system level determines whether preventive and/or corrective maintenance actions are needed based on the system's predictive reliability. At the component level, the optimal group of components for preventive maintenance is identified considering reliability improvement and maintenance cost.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Industrial
Mageed Ghaleb, Sharareh Taghipour, Hossein Zolfagharinia
Summary: This paper discusses the real-time joint optimization of maintenance planning and production scheduling in smart manufacturing systems. By using a modified hybrid genetic algorithm and other methods, it addresses common issues that occur in practice and shows the superiority of the proposed system in solving the problem under study. The results emphasize the importance of baseline plan quality, hybrid rescheduling policies, and reaction times for cost savings.
JOURNAL OF MANUFACTURING SYSTEMS
(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
Engineering, Industrial
Jordan L. Oakley, Kevin J. Wilson, Pete Philipson
Summary: This paper proposes a condition-based maintenance policy for multi-component systems that incorporate both stochastic and economic dependence, aiming to optimize replacement decisions. The policy includes a utility function that balances rewards of clustering component replacements with costs of load sharing. Through numerical studies, it is shown that this policy outperforms other alternative policies by reducing system life-cycle costs.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Automation & Control Systems
Michael Hoffman, Eunhye Song, Michael P. Brundage, Soundar Kumara
Summary: This study proposes a two-stage approach to address the problem of maintenance resource allocation, optimizing a static maintenance policy using a genetic algorithm initially, and then improving the policy online through Monte Carlo tree search to maximize production volume and resolve conflicts between maintenance and production objectives.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Interdisciplinary Applications
Marco Koopmans, Bram de Jonge
Summary: This study examines the value of condition-based production in industrial facilities and optimizes production and maintenance decisions. Numerical analysis shows that adjustable production speeds can be used to actively desynchronize the deterioration levels of units. Considerable profit increases are obtained by lowering the production speed in systems aiming to maximize total production output.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Yanyan Chang, Rengkui Liu, Yuanjie Tang
Summary: This paper proposes a novel operation-level maintenance scheduling framework based on segment condition, considering both opportunistic and centralized maintenance strategies. The effectiveness of the model and algorithm is verified through the design of a hybrid multi-objective optimization algorithm.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2023)
Article
Engineering, Industrial
Wenyu Zhang, Xiaohong Zhang, Shuguang He, Xing Zhao, Zhen He
Summary: This paper presents a maintenance modeling method for multi-component repairable systems (MCRS) and a maintenance decision model that minimizes the total cost within a finite time horizon. The results show that the proposed model is effective.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Operations Research & Management Science
Shadi Sanoubar, Bram de Jonge, Lisa M. Maillart, Oleg A. Prokopyev
Summary: This paper discusses the problem of condition-based maintenance on geographically distributed assets using a single maintenance resource. It dynamically determines the optimal positioning and timing of maintenance interventions based on asset conditions and the resource's current location. The study explores unique trade-offs, models the assets and resource using graphs, and formulates a Markov decision process to obtain the optimal policy for the maintenance resource.
TRANSPORTATION SCIENCE
(2023)
Article
Energy & Fuels
Jinhe Wang, Xiaohong Zhang, Jianchao Zeng
Summary: This study proposed a group maintenance strategy for the cost-effectiveness of a wind farm as a whole; determined the optimal inspection interval and number of failed wind turbines using a stationary probability density function; validated the correctness and effectiveness of the proposed strategy through numerical experiments and a case study.
Article
Engineering, Aerospace
Wim J. C. Verhagen, Bruno F. Santos, Floris Freeman, Paul van Kessel, Dimitrios Zarouchas, Theodoros Loutas, Richard C. K. Yeun, Iryna Heiets
Summary: The research aims to identify challenges and limitations in adopting CBM in aviation, as well as propose solutions and policy implications. The findings highlight the importance of addressing issues related to data quantity and quality, CBM implementation, and integration with future technologies in future research and practice.
Article
Statistics & Probability
Shakiba Bazeli, Mohammad Saber Fallahnezhad, Ahmad Sadegheih, Hasan Hosseini Nasab
Summary: This paper investigates the relationship between maintenance and product quality in a manufacturing system and proposes clustering maintenance actions to reduce failure frequency and impact on product quality. The results suggest that clustering perfect maintenance can be more optimal than imperfect maintenance.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2022)
Article
Engineering, Industrial
Alp Akcay, Engin Topan, Geert-Jan van Houtum
Summary: The study examines randomly failing high-precision machine tools in a discrete manufacturing setting, developing a Markov decision model to determine when to inspect or retire a tool in order to maximize total expected reward. Implementation using real-world maintenance logs at a Philips shaver factory demonstrates that the value of the optimal policy can be substantial compared to current practice.
Article
Engineering, Manufacturing
Bram Westerweel, Rob Basten, Jelmar den Boer, Geert-Jan van Houtum
Summary: This study explores the benefits of on-site printing of spare parts in remote geographic locations with intermittent spare parts supply and fixed interval replenishment. By considering emergency supply options and modeling replenishment decisions, it is found that on-site 3D printing leads to significant operational cost savings and increased asset availability compared to expediting. These results have implications for organizations operating in remote locations, such as the mining and offshore industry.
PRODUCTION AND OPERATIONS MANAGEMENT
(2021)
Article
Engineering, Industrial
Douniel Lamghari-Idrissi, Rob Basten, Geert-Jan van Houtum
Summary: This study investigates spare parts service contracts for capital goods and introduces a flexible-time contract as a solution, proving its advantages through simulation and a Markov decision process.
Article
Computer Science, Artificial Intelligence
S. Voorberg, R. Eshuis, W. van Jaarsveld, G. J. van Houtum
Summary: This paper introduces an approach that supports decision makers in balancing information gathering and cost-effective decision making, using CMMN modeling notation and Markov Decision Processes optimization technique to provide decision makers with an optimal information-gathering solution and configure a run-time recommendation tool.
DECISION SUPPORT SYSTEMS
(2021)
Article
Management
Ipek Dursun, Alp Akcay, Geert-Jan Van Houtum
Summary: The study focuses on applying an age-based replacement policy in a system with a finite lifespan to preventively replace a critical component before failure. It considers the decision maker's belief on the existence of a weak population and builds an optimal policy that balances the trade-off between cost and learning the true population type.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Management
S. Voorberg, W. van Jaarsveld, R. Eshuis, G. J. van Houtum
Summary: Component maintenance, repair and overhaul are conducted under long-term service agreements. Service providers need to make accurate estimations of contract values to win contracts and make profits. Therefore, collecting attributes from multiple sources to improve knowledge about specific contracts is crucial. This paper introduces a model for optimal information acquisition and a specific model refinement for quotation optimization. Three heuristic policies with different levels of dynamism are proposed. Fixing the order in which attributes are retrieved has a small impact on profit, while fixing the number of attributes has worse consequences.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Editorial Material
Operations Research & Management Science
Frank P. A. Coolen, Tahani Coolen-Maturi, Geert-Jan van Houtum
APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY
(2023)
Article
Engineering, Industrial
Ipek Dursun, Alp Akcay, Geert-Jan Van Houtum
Summary: This study considers multiple single-component systems with a known finite lifespan and investigates the optimal replacement policy to minimize cost. Expert opinions are used to estimate the component lifetime distribution, while uncertainty regarding population heterogeneity is resolved through data pooling. Numerical experiments demonstrate significant cost reduction through data pooling.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2022)
Article
Engineering, Industrial
Halit Metehan Dilaver, Alp Akcay, Geert-Jan van Houtum
Summary: In the maritime industry, obligatory inspections and maintenance operations on moving assets are conducted based on calendar time and usage-based deterioration respectively. Synchronizing these operations to avoid unnecessary dry-dockings is a common approach, but determining the optimal timing and synchronization remains a crucial question. This real-life problem is formulated as a mixed integer linear programming model, which demonstrates that integrated planning can save up to 28.5% of the total cost.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2023)
Article
Management
Erhun Ozkan, Geert-Jan van Houtum
Summary: This study focuses on the inventory and repair scheduling decisions of a maintenance service provider for repairable capital goods. The objective is to minimize the long-run average inventory holding, back-order, and emergency repair costs. The study formulates the repairable network as a closed queueing system and solves a Brownian control problem to derive an optimal decision rule.
OPERATIONS RESEARCH
(2023)
Article
Business
Fiona Sloothaak, Alp Akcay, Geert-Jan van Houtum, Matthieu van der Heijden
Summary: In this study, we propose a continuous-time model to optimize the upgrade decisions of a system during the fixed lifetime of the asset. The model considers important factors such as increasing functionality requirements, age-dependent maintenance costs, a predetermined overhaul plan, and the lifetime of the asset. We analyze the optimal upgrade policy under different cost functions and propose a dynamic programming approach for cases with penalties for upgrading outside an overhaul. Surprisingly, more overhauls may lead to a smaller number of upgrades under the optimal policy.
Article
Operations Research & Management Science
Joni Driessen, Joost de Kruijff, Joachim Arts, Geert-Jan van Houtum
Summary: This article investigates the design problem of line replaceable units (LRUs) and proposes two solving methods using set partitioning and binary linear programming. It considers the costs of replacement, downtime, and purchase/repair, and examines the effects of parameters on the model's outcome.
NAVAL RESEARCH LOGISTICS
(2023)
Article
Engineering, Industrial
Ragnar Eggertsson, Rob Basten, Geert-Jan van Houtum
Summary: This study focuses on the inspection and maintenance planning of capital goods, taking into account the imprecise observations and their dependence on the environment. Through the example of HVAC maintenance on trains, it is demonstrated that an environment-dependent policy can lead to cost savings.
Proceedings Paper
Computer Science, Theory & Methods
Joan Stip, Lois Aerts, Geert-Jan van Houtum
Summary: To minimize costs and meet service level agreements, Original Equipment Manufacturers (OEMs) use spare parts planning models to determine optimal base stock levels at their warehouses. However, there is often a deviation between the expected and realized performance of these optimized stock levels. In order to evaluate this performance and identify root causes for the gap, a digital twin has been developed. This digital twin has helped one semiconductor industry OEM, ASML, create a feedback loop to learn from past results and close the gap between expected and realized performance.
2022 WINTER SIMULATION CONFERENCE (WSC)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Nikki Theeuwes, Geert-Jan Van Houtum, Yingqian Zhang
Summary: This paper presents a case study conducted in a Dutch EMS region to improve ambulance dispatching. By enhancing the current dispatch policy with redispatching and reevaluation policies, the on-time performance of highly urgent ambulance requests was improved by 0.77% points, which is equivalent to adding seven weekly ambulance shifts.
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2021: APPLIED DATA SCIENCE TRACK, PT IV
(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)