Article
Mathematics
Fanping Wei, Jingjing Wang, Xiaobing Ma, Li Yang, Qingan Qiu
Summary: Information-driven group maintenance is crucial for enhancing the availability and profitability of industrial systems. However, existing models have focused on a single health criterion and rarely integrated multiple criteria. This study addresses these gaps by proposing a multiple-information-driven replacement policy for serial systems.
Article
Operations Research & Management Science
Junyuan Wang, Jimin Ye, Liang Wang
Summary: In this paper, extended preventive replacement models for series and parallel system with n independent non-identical components are proposed. The models consider two types of failure and offer different options for replacement. The average cost rate function and failure rate function under different cases are obtained. The optimal preventive replacement time based on minimizing the average cost rate function is also determined. Numerical examples are provided for cost evaluation and performance verification.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Computer Science, Information Systems
Ahmet Kolus
Summary: The objective of this study is to integrate human factors that affect maintenance performance in delay-time modelling to obtain an accurate and realistic optimal inspection interval. A list of human factors is identified through a literature review and three significant factors are selected to be incorporated into the model. Fuzzy modeling is used to estimate a time allowance for human factors. Two inspection models are developed and validated against a realistic case study. The results show that failing to account for human factors increases inspection frequency and interruptions of production, resulting in decreased inspection time and operator performance. The developed models and conceptual framework can help decision makers set an accurate inspection duration and design maintenance systems with superior long-term performance.
Article
Engineering, Multidisciplinary
Yan R. Melo, Cristiano A. Cavalcante, Phil Scarf, Rodrigo S. Lopes
Summary: This study proposes a maintenance policy for remote systems that combines periodic inspection and opportunistic replacement. The results indicate that opportunistic replacement can significantly impact the cost-rate of the optimum policy but cannot achieve very high availability. Therefore, maintenance planning should be flexible when external factors influence maintenance effectiveness.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY
(2023)
Article
Engineering, Industrial
Fengxia Zhang, Jingyuan Shen, Haitao Liao, Yizhong Ma
Summary: This paper investigates a two-phase imperfect inspection strategy combined with a hybrid preventive maintenance policy for a three-state system, and illustrates the advantages of the method through numerical examples.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Engineering, Industrial
Cristiano A. Cavalcante, Rodrigo S. Lopes, Philip A. Scarf
Summary: The study focuses on an inspection and replacement policy for systems, emphasizing what maintenance to schedule at known times rather than when to schedule maintenance. The model considers limitations in time and resources that may lead to violations. Results show that the scheduled time for preventive replacement and the effective visit-frequency have the largest effect on policy performance.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Engineering, Industrial
Elizabeth Bismut, Daniel Straub
Summary: This paper presents a heuristic-based approach using simple decision rules to optimize inspection and maintenance plans for large structures. The method involves adaptive planning to continuously adjust the initial I&M plan throughout the service life based on past inspection and monitoring results.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Engineering, Industrial
Rui Peng, Xiaofeng He, Chao Zhong, Gang Kou, Hui Xiao
Summary: This research discusses the optimal maintenance policies considering multiple failure modes in parallel systems and evaluates their applications through simulation experiments. The findings provide valuable insights for choosing the best policy.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Engineering, Aerospace
Vladimir Ulansky, Ahmed Raza
Summary: Maintenance is crucial for long-term overall equipment effectiveness, and evaluating its effectiveness is essential. This study provides classifications for selecting maintenance effectiveness indicators and calculating them. The classification of systems is based on signs such as system maintainability, failure consequences, economic assessment of failure consequences, and system use. The classification of maintenance models considers factors like system reliability, inspection type, unit restoration degree, and external failure manifestations. The study demonstrates that condition-based maintenance significantly improves availability and reduces inspections compared to corrective maintenance.
Article
Engineering, Multidisciplinary
Yen-Luan Chen, Chin-Chih Chang, Zhe George Zhang, Xiaofeng Chen
Summary: This paper introduces modified preventive maintenance policies for an operating system that operates at random processing times and is imperfectly maintained. The system may experience two types of failures based on a time-dependent imperfect maintenance mechanism. Two maintenance policies, preventive maintenance-first (PMF) and preventive maintenance-last (PML), are applied to the system, with the optimal preventive maintenance schedule derived and determined analytically and numerically. The proposed models offer a general framework for analyzing maintenance policies in reliability theory.
JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION
(2021)
Article
Engineering, Industrial
Jiantai Wang, Shihan Zhou, Rui Peng, Qingan Qiu, Li Yang
Summary: Inspection is essential in asset management to uncover defects and monitor equipment health. However, imperfect inspections due to technical or human errors challenge decision-making optimality. This study investigates an inspection-based replacement strategy for continuous deteriorating systems, accounting for inspection errors. The non-steady evolution trajectory is captured using a piecewise stochastic process, with inspections equally spaced to reveal system state but with a probability of missing defects. Control limits are scheduled to adjust replacement frequencies, and a cost model is optimized. A case study on high-speed train bearings demonstrates the effectiveness of the proposed strategy, reducing costs by 39% and 4% compared to two conventional policies.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Computer Science, Interdisciplinary Applications
M. D. Berrade, E. Calvo, F. G. Badia
Summary: We propose a model for inspecting and maintaining systems with two types of failures. The model considers early failures caused by weak critical components and age-related failures addressed by preventive maintenance. The unique aspects of this model are the use of defective distribution to model defect-free strong components and the removal of weak critical parts without rejuvenation, serving as a minimal repair alternative. We analyze the conditions under which this model outperforms other classical age-replacement models in terms of cost, and provide insights on the proportion of weak units and the quality of inspections for optimum maintenance policy decision-making. A case study on the timing belt of a four-stroke engine demonstrates the application of the model.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Engineering, Industrial
Gehui Liu, Shaokuan Chen, Hua Jin, Shuang Liu
Summary: The study introduces a maintenance optimization model to improve system reliability and save maintenance costs. It proposes the delay time theory for evaluating system reliability and develops a comprehensive maintenance model for multi-level maintenance actions. The applicability of the model and the efficiency of the algorithm are demonstrated through case studies.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Operations Research & Management Science
Pradipta Patra, U. Dinesh Kumar
Summary: Availability contracting is an important procurement strategy in defense and capital equipment industry. This paper extends the classical operational availability model and develops optimization models for finding the optimal availability contract duration. The study shows that the optimal contract duration is influenced by spares on hand and the inherent availability of system part. The results have been validated using simulated and real data.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Management
Thijs Nicolaas Schouten, Rommert Dekker, Mustafa Hekimoglu, Ayse Sena Eruguz
Summary: This paper introduces a new model for maintenance optimization in offshore wind turbine maintenance, which addresses time-varying costs. The authors extend the standard maintenance policies and prove that the optimal maintenance policy under time-varying costs is a time-dependent strategy. They also present linear programming models for parameter optimization. By applying these models, they demonstrate significant cost savings in maintenance planning.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
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
Green & Sustainable Science & Technology
Ben Purvis, Dilay Celebi, Mario Pansera
Summary: Approaching the transition to a Circular Economy (CE) through a 'just transition' perspective requires prioritizing stakeholder knowledge and agency. In this paradigm, the move towards a CE is viewed as a socio-economic transformation grounded in principles of social and environmental justice, rather than a mere technocratic challenge. Responsible Research and Innovation (RRI), as an approach that considers the relationship between science and society, including concepts of anticipation, inclusion, reflection, and responsiveness, can help integrate considerations of justice into CE practices. By critically exploring these dimensions and addressing the often overlooked issue of who benefits from the transition to a CE, we propose a framework for designing responsible CE practices, which can serve as a starting point for refining the decision-making context faced by relevant groups.
JOURNAL OF CLEANER PRODUCTION
(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.
Article
Transportation Science & Technology
Sukru Imre, Dilay Celebi, Umut Asan
Summary: This research analyzes the factors influencing the preference for electric vehicles in urban freight transport and estimates their potential adoption. The findings suggest that electric vehicles could significantly reduce CO2 emissions in delivery operations.
TRANSPORTATION PLANNING AND TECHNOLOGY
(2023)
Article
Transportation
Dilay Celebi
Summary: This study explores the current status and challenges of rail freight transportation in Turkey and aims to propose solutions and improve competitiveness. The research utilizes various methods such as structured interviews and case studies to analyze the current landscape and identify viable strategies for enhancing competitiveness. The findings highlight the urgency of reforms in Turkey's railway sector and emphasize the importance of improved investment planning and resource utilization efficiency.
CASE STUDIES ON TRANSPORT POLICY
(2023)
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)