现代制造工程 ›› 2025, Vol. 540 ›› Issue (9): 12-19.doi: 10.16731/j.cnki.1671-3133.2025.09.002

• 先进制造系统管理运作 • 上一篇    下一篇

基于改进蛇优化算法的柔性作业车间调度研究

朱敏1,2, 王岩1, 卞京1, 卢宇涵1   

  1. 1 合肥工业大学电气与自动化工程学院,合肥 230009;
    2 工业自动化安徽省工程技术研究中心,合肥 230009
  • 收稿日期:2024-09-19 出版日期:2025-09-18 发布日期:2025-09-23
  • 作者简介:朱敏,副教授,硕士研究生导师,主要研究方向为复杂系统建模与控制。王岩,硕士研究生,主要研究方向为智能装备与制造。卞京,硕士研究生,主要研究方向为控制工程。卢宇涵,本科,主要研究方向为机器人工程。E-mail:zhumin71@126.com。
  • 基金资助:
    国家自然科学基金项目(62073113)

Research on flexible job shop scheduling based on improved snake optimization algorithm

ZHU Min1,2, WANG Yan1, BIAN Jing1, LU Yuhan1   

  1. 1 School of Electrical and Automation Engineering,Hefei University of Technology,Hefei 230009,China;
    2 Anhui Provincial Engineering Technology Research Center for Industrial Automation,Hefei 230009,China
  • Received:2024-09-19 Online:2025-09-18 Published:2025-09-23

摘要: 针对柔性作业车间调度问题(Flexible Job shop Scheduling Problem,FJSP),以优化最大完工时间为目标,提出了一种改进蛇优化(Improved Snake Optimization,ISO)算法。该算法对蛇优化算法进行研究,使用两段式编码替代原算法的实数编码,使得改进后的蛇优化算法可以在离散空间中对蛇个体的位置进行更新。此外,针对原算法中初始种群质量较低的问题,采用GLR策略平衡机器加工负荷,以提高算法的初始化质量。并针对原算法中蛇个体的位置变化与交互机制,在保留原有蛇群演化的基础上使用2个操作算子对其进行重新设计。最后,使用正交实验分析算法参数,并对车间的15个基准算例和1个案例进行仿真和对比,验证了所提算法求解该问题的有效性和稳定性。

关键词: 柔性作业车间调度, 离散优化问题, 改进蛇优化算法

Abstract: Aiming at optimizing the maximum completion time for Flexible Job Shop Scheduling Problem (FJSP), it proposes an Improved Snake Optimization (ISO) algorithm. This algorithm studies the snake optimization algorithm and uses two-stage coding to replace the real coding of the original algorithm, so that the improved snake optimization algorithm can update the position of the individual snake in the discrete space. In addition, to solve the problem of low initial population quality in the original algorithm, GLR strategy is used to balance the machining load to improve the initialization quality of the algorithm. The position change and interaction mechanism of individual snake in the original algorithm are redesigned by using two operators on the basis of preserving the evolution of the original snake group. Finally, the orthogonal experiment is used to analyze the algorithm parameters, and 15 benchmark examples and 1 case in the workshop are simulated and compared to verify the effectiveness and stability of the proposed algorithm to solve the problem.

Key words: flexible job shop scheduling, discrete optimization problem, improved snake optimization algorithm

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