Article
Mathematics
Hongyu He, Yanzhi Zhao, Xiaojun Ma, Zheng-Guo Lv, Ji-Bo Wang
Summary: This paper focuses on green scheduling to enhance efficiency by optimizing resource allocation and job sequencing. It proposes a branch-and-bound algorithm and heuristic algorithms to solve the problem and validates their effectiveness through numerical experiments.
Article
Mathematics
Yi-Chun Wang, Si-Han Wang, Ji-Bo Wang
Summary: This paper investigates a single machine common due-window assignment scheduling problem with position-dependent weights and resource allocations under just-in-time production. The actual processing time of a job is determined by the resource allocated to it. The resource allocation model is divided into linear and convex allocations. The goal is to find an optimal due-window location, job sequence, and resource allocation. The study proves that the minimization of weighted sum of scheduling cost and resource consumption cost can be solved in polynomial time. Furthermore, under convex resource allocation, the minimization of scheduling or resource consumption cost is solvable in polynomial time with bounded cost.
Article
Mathematics, Applied
Wanlei Wang
Summary: This paper investigates the single-machine due-date assignment problem with past-sequence-dependent setup times, proposing optimal solutions under different due-date assignment scenarios. The problem is proven to be solvable in polynomial time by minimizing a linear weighted sum. Furthermore, three extensions are provided by considering various dependencies in processing times.
JOURNAL OF APPLIED MATHEMATICS AND COMPUTING
(2022)
Article
Engineering, Multidisciplinary
Wen-Tso Huang, Ping-Shun Chen, Gary Yu-Hsin Chen, Jr-Fong Dang
Summary: This study extends the common due date problem to the dynamic flow shop environment and proposes an enhanced heuristic algorithm to solve the minimum penalty value, which outperforms previous conventional CDDA and EDD in average penalties.
MATHEMATICAL PROBLEMS IN ENGINEERING
(2022)
Article
Operations Research & Management Science
Chen Xu, Yinfeng Xu, Feifeng Zheng, Ming Liu
Summary: The study focuses on multitasking scheduling and due-window assignment problems in a single machine. Two objectives are studied in the paper, with analytical properties and polynomial time solutions provided for optimal results. Experimental results demonstrate the effectiveness of the proposed methods.
RAIRO-OPERATIONS RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Oguzhan Ahmet Arik, Marco Schutten, Engin Topan
Summary: This paper investigates an unrelated parallel machine scheduling problem with a restrictive common due date and proposes construction-based heuristics and local search algorithms to minimize earliness/tardiness costs. By optimizing start times of machines and job assignment patterns, it achieves a balanced workload per machine and outperforms metaheuristics in solution quality.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Mathematics, Applied
Jin Qian, Haiyan Han
Summary: This paper discusses the single machine scheduling problem with three different due dates, where the actual processing time of the job deteriorates as the starting time increases. The goal is to minimize total costs by considering earliness, tardiness, and due date. The study proves that these problems can be solved in polynomial time and proposes algorithms to obtain the optimal sequence and due date.
JOURNAL OF APPLIED MATHEMATICS AND COMPUTING
(2022)
Article
Mathematics
Jin Qian, Yu Zhan
Summary: This paper discusses the scheduling problem for a single machine, taking into account due window, delivery time, and deteriorating jobs. The objective is to minimize the window location, window size, earliness, and tardiness. Both common due window and slack due window are considered. The delivery time depends on the actual processing time of previous sequences, which is an increasing function of the start time. By utilizing small perturbations and adjacent exchange techniques, propositions for the problems are obtained. Polynomial time solvability in O(nlogn) time is proven for both common and slack due window assignment. The paper also proposes algorithms to obtain the optimal sequence, window location, and window size.
Article
Engineering, Industrial
Jeffrey Schaller, Jorge M. S. Valente
Summary: This paper addresses the scheduling of jobs in a no-wait flow shop with the goal of minimizing total earliness and tardiness. Various dispatching heuristics and insertion improvement procedures are developed and tested, showing that the two-phase heuristics and insertion search improvement procedure can significantly improve performance.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Mathematics, Interdisciplinary Applications
Oguzhan Ahmet Arik
Summary: This paper presents a mixed-integer programming model for a single machine earliness/tardiness scheduling problem aiming to minimize total earliness/tardiness duration. The uncertainty of parameters such as processing times and due date is coded with grey numbers, and an effective heuristic method is proposed using expected processing times. The research contributes to the literature by utilizing grey theory and numbers in machine scheduling problems.
GREY SYSTEMS-THEORY AND APPLICATION
(2021)
Article
Engineering, Multidisciplinary
Xiaohong Zhang, Zhe Zhang, Xiaoling Song, Xue Gong, Yong Yin
Summary: This paper focuses on the scheduling problem in Seru production system, considering sequence dependent setup time and release date. A mixed integer programming model and a branch and-bound algorithm are proposed, and computational experiments are conducted. The results show that the proposed algorithm performs well in finding high-quality solutions quickly.
JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION
(2023)
Article
Engineering, Industrial
Mohammad Namakshenas, Aleida Braaksma, Mohammad Mahdavi Mazdeh
Summary: This study addresses a class of resource-constrained scheduling problems with non-renewable resources supplied in different periods, aiming to minimize total tardiness and total earliness. The optimal schedules are discussed and a tractable algorithm is developed, showing promising performance guarantee in scalability tests.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Weishi Shao, Zhongshi Shao, Dechang Pi
Summary: This paper studies a multiobjective distributed hybrid flow shop scheduling problem (MDHFSP) and proposes a multi-objective evolutionary algorithm to solve it, optimizing solutions effectively through multiple neighborhoods local search operators and an adaptive weight updating mechanism.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Interdisciplinary Applications
Fuli Xiong, Mengling Chu, Zhi Li, Yao Du, Linting Wang
Summary: This paper focuses on the distributed concrete precast flow shop scheduling problem, proposing a novel mixed integer linear programming model and solving the NP-hard problem by iterated greedy algorithm and tabu search algorithm. The computational analysis shows the effectiveness of the proposed algorithms.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Ziye Zhao, Xiaohui Chen, Youjun An, Yinghe Li, Kaizhou Gao
Summary: To maximize profitability and customer satisfaction, this study focuses on the order acceptance and scheduling (OAS) problem in a make-to-order environment. A mathematical model is established to consider earliness/tardiness penalty under a common due window and maximize total net profit (TNP). Problem-specific properties are derived to determine which orders to accept and the processing sequence and start processing time for accepted orders. An efficient hybrid algorithm (GATS-SSRIR) is designed, combining genetic algorithm, tabu search, and problem-specific properties. Numerical experiments validate the effectiveness of the proposed properties and the superiority of the GATS-SSRIR algorithm, with average improvements of 45.3% and 67.3% respectively. Sensitivity analysis reveals the significant impact of the due window on TNP.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
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)