Research on Optimization of Enterprise Production Line Based on Genetic Algorithm

Chengjun Ji () and Liangliang Hu
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Chengjun Ji: Liaoning Technical University
Liangliang Hu: Liaoning Technical University

A chapter in Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023), 2024, pp 512-517 from Springer

Abstract: 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.

Keywords: Genetic algorithm; Enterprise production line; Optimization; Fitness function; Cross over; Variation; To choose; Iterative optimization; Production efficiency; Economic benefits (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-256-9_52

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DOI: 10.2991/978-94-6463-256-9_52

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