A novel multi-objective optimization algorithm for the integrated scheduling of flexible job shops considering preventiv
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METHODOLOGIES AND APPLICATION
A novel multi-objective optimization algorithm for the integrated scheduling of flexible job shops considering preventive maintenance activities and transportation processes Hui Wang1 Gaocai Fu1
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Buyun Sheng1 • Qibing Lu1 • Xiyan Yin1 • Feiyu Zhao1 • Xincheng Lu1 • Ruiping Luo1
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Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Most production scheduling problems, including standard flexible job shop scheduling problems, assume that machines are continuously available. However, in most cases, due to preventive maintenance activities, machines may not be available for a certain time. Meanwhile, in the entire workshop production process, the transportation process of workpieces cannot be ignored. Therefore, the impact of transportation on the production planning should be considered in the scheduling process. To consider both preventive maintenance and transportation processes in the flexible job shop scheduling problem, this paper proposes a flexible job shop scheduling problem considering preventive maintenance activities and transportation processes and establishes a multi-objective flexible job shop scheduling model optimizing the total energy consumption and total makespan. Furthermore, a multi-region division sampling strategy-based multi-objective optimization algorithm integrated with a genetic algorithm and a differential evolution algorithm (MDSS-MOGA-DE) is proposed to solve the model. In the proposed algorithm, a multi-region division sampling strategy and two evaluation functions are utilized to improve the diversity of solutions. In addition, this paper combines a genetic operation and a differential operation to further enhance the search ability of the algorithm. The validity of the algorithm is verified by a real case. The computational results reveal that the proposed model and algorithm obtain appropriate results and have the potential to be applied to other similar problems. Keywords Flexible job shop scheduling problem Preventive maintenance activities Transportation process Multi-objective optimization Multi-region division sampling strategy
1 Introduction The job shop scheduling problem is a key issue in the field of production and manufacturing and has critical significance on engineering applications and academic research (Naderi et al. 2011; Bagheri et al. 2010; Jamili 2016). The classical job shop scheduling problem can be described as: I jobs will be processed on K machines, where each job has multiple processes and each process can only be processed by one machine. In addition, each machine can only Communicated by V. Loia. & Hui Wang [email protected] 1
School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, Hubei, China
process one job at a time. The purpose of this scheduling problem is to determine the sequence of different jobs processed on each machine. Meanwhile, it also needs to satisfy predefined optimization objectives, such as
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