Computer Engineering and Applications ›› 2019, Vol. 55 ›› Issue (23): 15-21.DOI: 10.3778/j.issn.1002-8331.1908-0410

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Review of Application of Genetic Algorithms for Solving Flexible Job Shop Scheduling Problems

LUO Xiong, QIAN Qian, FU Yunfa   

  1. School of Information Engineering and Automation, Yunnan Key Laboratory of Computer Technology Applications, Kunming University of Science and Technology, Kunming 650500, China
  • Online:2019-12-01 Published:2019-12-11



  1. 昆明理工大学 信息工程与自动化学院,云南省计算机技术应用重点实验室,昆明 650500

Abstract: The flexible job shop scheduling problem is a typical NP-hard problem, which can guide the actual production of factories. In recent years, with the development of genetic algorithms, the ideas and methods of using genetic algorithms to solve flexible job shop scheduling problems are emerging in an endless stream. In order to promote the further development of genetic algorithm for flexible job shop scheduling problem, this paper first introduces the research theory of flexible job shop scheduling problem, and then classifies existing improved methods that are based on genetic algorithms. In the end, by analyzing the existing problems, several future research directions are proposed.

Key words: flexible job shop scheduling problem;genetic algorithm, objective function, algorithm improvement

摘要: 柔性作业车间调度问题是典型的NP难问题,对实际生产应用具有指导作用。近年来,随着遗传算法的发展,利用遗传算法来解决柔性作业车间调度问题的思想和方法层出不穷。为了促进遗传算法求解柔性作业车间调度问题的进一步发展,阐述了柔性作业车间调度问题的研究理论,对已有改进方法进行了分类,通过对现存问题的分析,探讨了未来的发展方向。

关键词: 柔性作业车间调度问题, 遗传算法, 目标函数, 算法改进