Proceedings of the 2022 4th International Conference on Economic Management and Cultural Industry (ICEMCI 2022)

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Research on Flexible Flow-shop batch scheduling based on improved Genetic Algorithm

Authors
Zexing Zhu1, *, Jiahui Chai1
1Institute of Economics and Management, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu, China
*Corresponding author. Email: hss152210413105@163.com
Corresponding Author
Zexing Zhu
Available Online 27 December 2022.
DOI
10.2991/978-94-6463-098-5_9How to use a DOI?
Keywords
Flexible flow shop; Optimized batching strategy; Improved genetic algorithm with two-layer frame
Abstract

In this paper, the batch scheduling problem of multi-stage flexible flow shop in mixed-flow production is studied. Considering the factors of parallel machine scheduling and equipment adjustment time, an integrated equal and variable optimal batch strategy is proposed. On this basis, a batch scheduling model is constructed to minimize the completion period, maximum load and total tardiness, and an improved genetic algorithm based on two-layer search framework is designed to solve the problem. In order to obtain a better scheduling scheme, the algorithm adopts three-stage coding and decoding considering adjustment time, and introduces the critical chain method and the minimum critical ratio rule through the integrated iterative process of inner algorithm and outer batch. The example results show that compared with the original scheme, the optimized scheduling scheme can effectively reduce the completion cycle by 10.35% and the order delay ratio by 40%. At the same time, the production line adjustment frequency is reduced by 22.45% compared with the scheme under equal division strategy. According to the above results, the applicability and effectiveness of the optimized batching strategy and the improved algorithm are verified.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 4th International Conference on Economic Management and Cultural Industry (ICEMCI 2022)
Series
Advances in Economics, Business and Management Research
Publication Date
27 December 2022
ISBN
78-94-6463-098-5
ISSN
2352-5428
DOI
10.2991/978-94-6463-098-5_9How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Zexing Zhu
AU  - Jiahui Chai
PY  - 2022
DA  - 2022/12/27
TI  - Research on Flexible Flow-shop batch scheduling based on improved Genetic Algorithm
BT  - Proceedings of the 2022 4th International Conference on Economic Management and Cultural Industry (ICEMCI 2022)
PB  - Atlantis Press
SP  - 65
EP  - 74
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-098-5_9
DO  - 10.2991/978-94-6463-098-5_9
ID  - Zhu2022
ER  -