Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 12
3690-3695

Improved hybrid multi-objective ant colony optimization for flexible Job-Shop scheduling problem with transportation time and setup time

Zhang Guohuia
Yan Shaofenga
Lu Xixia
Zhang Haijunb
a. School of Management Engineering, b. School of Aeronautics & Astronautics, Zhengzhou University of Aeronautics, Zhengzhou 450046, China
DOI: 10.19734/j.issn.1001-3695.2022.10.0546

Abstract

Flexible job shop scheduling is an important combinatorial optimization problem. In the actual production process, there are transportation time and setup time in indirect processing activities such as product handling, and machine tool changing, which will affect the production cycle. This paper studied the flexible job shop scheduling problem considering both transportation time and setup time, established a mathematical model with the objectives of minimizing the maximum completion time, total workload, the workload of the critical machine, and penalties of earliness/tardiness, and proposed an improved hybrid multi-objective ant colony optimization. It designed a distributed coding method by combining the problem characteristics and algorithm features, using an improved ant colony optimization to search for the optimal scheduling solution for each optimization objective separately, performing non-dominated sorting selection for the set of scheduling solutions, and proposing mutation and closeness operations in order to improve the search accuracy of the algorithm. Finally, it conducted simulation experiments using benchmark and production instance and compared them with the improved genetic algorithm and MOGATS algorithm, and the experimental results showed that the proposed improved hybrid multi-objective ant colony optimization is effective and feasible.

Foundation Support

国家自然科学基金资助项目(U1904167)
河南省高校科技创新团队(21IRTSTHN018)
郑州航院研究生教育创新计划基金资助项目(2022CX22)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.10.0546
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 12
Section: Algorithm Research & Explore
Pages: 3690-3695
Serial Number: 1001-3695(2023)12-026-3690-06

Publish History

[2023-01-04] Accepted Paper
[2023-12-05] Printed Article

Cite This Article

张国辉, 闫少峰, 陆熙熙, 等. 改进混合多目标蚁群算法求解带运输时间和调整时间的柔性作业车间调度问题 [J]. 计算机应用研究, 2023, 40 (12): 3690-3695. (Zhang Guohui, Yan Shaofeng, Lu Xixi, et al. Improved hybrid multi-objective ant colony optimization for flexible Job-Shop scheduling problem with transportation time and setup time [J]. Application Research of Computers, 2023, 40 (12): 3690-3695. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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