Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023)

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Research on Optimization of Enterprise Production Line Based on Genetic Algorithm

Authors
Chengjun Ji1, *, Liangliang Hu1
1Liaoning Technical University, Fuxin, China
*Corresponding author. Email: 18855066855@qq.com
Corresponding Author
Chengjun Ji
Available Online 9 October 2023.
DOI
10.2991/978-94-6463-256-9_52How to use a DOI?
Keywords
Genetic algorithm; Enterprise production line; Optimization; Fitness function; Cross over; Variation; To choose; Iterative optimization; Production efficiency; Economic benefits
Abstract

The purpose of this paper is to study how to optimize the production line of enterprises by using genetic algorithm, so as to improve the production efficiency and economic benefit of enterprises. In this study, we apply genetic algorithm to the production line optimization problem. Through the understanding and application of basic genetic algorithm, the optimization objective is transformed into a fitness function, and the operation of crossover, mutation and selection is used to optimize the fitness function. We divided the optimization process into two stages: the generation of initial population and the iterative optimization of genetic algorithm. Through experiments, we verify the effectiveness of genetic algorithm in the production line optimization problem, and draw a conclusion: genetic algorithm can effectively optimize the production line, improve production efficiency and economic benefits.

Copyright
© 2024 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 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023)
Series
Advances in Economics, Business and Management Research
Publication Date
9 October 2023
ISBN
10.2991/978-94-6463-256-9_52
ISSN
2352-5428
DOI
10.2991/978-94-6463-256-9_52How to use a DOI?
Copyright
© 2024 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  - Chengjun Ji
AU  - Liangliang Hu
PY  - 2023
DA  - 2023/10/09
TI  - Research on Optimization of Enterprise Production Line Based on Genetic Algorithm
BT  - Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023)
PB  - Atlantis Press
SP  - 512
EP  - 517
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-256-9_52
DO  - 10.2991/978-94-6463-256-9_52
ID  - Ji2023
ER  -