Multiobjective unrelated parallel machines scheduling problem with periodic maintenance activities and dependent processing times

被引:0
作者
Yaghtin, Mohammad [1 ]
Javid, Youness [1 ]
机构
[1] Kharazmi Univ, Fac Engn, Dept Ind Engn, Tehran, Iran
关键词
Parallel machine scheduling; Periodic maintenance activities; Multiobjective; NSGA-II; PREVENTIVE MAINTENANCE; GENETIC ALGORITHM; AVAILABILITY; OPTIMIZATION; JOBS; MINIMIZATION; RESOURCES; TARDINESS;
D O I
10.1108/JM2-09-2023-0198
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Purpose - The purpose of this research is to address the complex multiobjective unrelated parallel machine scheduling problem with real-world constraints, including sequence-dependent setup times and periodic machine maintenance. The primary goal is to minimize total tardiness, earliness and total completion times simultaneously. This study aims to provide effective solution methods, including a Mixed-Integer Programming (MIP) model, an Epsilon-constraint method and the Nondominated Sorting Genetic Algorithm (NSGA-II), to offer valuable insights into solving large-sized instances of this challenging problem. Design/methodology/approach - This study addresses a multiobjective unrelated parallel machine scheduling problem with sequence-dependent setup times and periodic machine maintenance activities. An MIP model is introduced to formulate the problem, and an Epsilon-constraint method is applied for a solution. To handle the NP-hard nature of the problem for larger instances, an NSGA-II is developed. The research involves the creation of 45 problem instances for computational experiments, which evaluate the performance of the algorithms in terms of proposed measures. Findings - The research findings demonstrate the effectiveness of the proposed solution approaches for the multiobjective unrelated parallel machine scheduling problem. Computational experiments on 45 generated problem instances reveal that the NSGA-II algorithm outperforms the Epsilon-constraint method, particularly for larger instances. The algorithms successfully minimize total tardiness, earliness and total completion times, showcasing their practical applicability and efficiency in handling real-world scheduling scenarios. Originality/value - This study contributes original value by addressing a complex multiobjective unrelated parallel machine scheduling problem with real-world constraints, including sequence-dependent setup times and periodic machine maintenance activities. The introduction of an MIP model, the application of the Epsilon-constraint method and the development of the NSGA-II algorithm offer innovative approaches to solving this NP-hard problem. The research provides valuable insights into efficient scheduling methods applicable in various industries, enhancing decision-making processes and operational efficiency.
引用
收藏
页码:477 / 494
页数:18
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