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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 7
2060-2067,2074

Improved grey wolf optimization algorithm for fuzzy Job-Shop scheduling problem

Cheng Jinhai
Xu Hua
Yang Jinfeng
School of Artificial Intelligence & Computer Science, Jiangnan University, Wuxi Jiangsu 214122, China
DOI: 10.19734/j.issn.1001-3695.2022.11.0515

Abstract

Fuzzy Job-Shop scheduling problem is a classic embodiment of complex scheduling, and an excellent scheduling scheme designed for this problem can improve production efficiency. At present, the research on fuzzy Job-Shop scheduling problem mainly focused on single objective, this paper proposed an improved grey wolf optimization(IGWO) algorithm to solve the bi-objective fuzzy flexible Job-Shop scheduling problem to minimize the fuzzy completion time and the total load of fuzzy machines. This algorithm proposed a two-layer coding method to make IGWO discretization, designed a strategy based on HV contribution degree to improve population diversity. Then it used reinforcement learning method to determine global and local search parameters, improved two crossover operators to help individuals evolve in different update modes, and used two-level variable neighborhood and four replacement strategies to improve local search capability. Finally, this paper carried out several groups of experiments on several examples to verify the effectiveness of the improved strategy. In most test cases, the performance of IGWO algorithm is better than the comparison algorithm, with good convergence and distribution.

Foundation Support

国家自然科学基金资助项目(62106088)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.11.0515
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 7
Section: Algorithm Research & Explore
Pages: 2060-2067,2074
Serial Number: 1001-3695(2023)07-021-2060-08

Publish History

[2023-01-06] Accepted Paper
[2023-07-05] Printed Article

Cite This Article

成金海, 徐华, 杨金峰. 改进灰狼优化算法求解模糊车间调度问题 [J]. 计算机应用研究, 2023, 40 (7): 2060-2067,2074. (Cheng Jinhai, Xu Hua, Yang Jinfeng. Improved grey wolf optimization algorithm for fuzzy Job-Shop scheduling problem [J]. Application Research of Computers, 2023, 40 (7): 2060-2067,2074. )

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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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