中国机械工程 ›› 2026, Vol. 37 ›› Issue (7): 1708-1716.DOI: 10.3969/j.issn.1004-132X.2026.07.020

• 智能制造 • 上一篇    

考虑运输资源限制的动态柔性车间调度问题及自适应竞争重构算法

王聪1,2(), 魏立新1,2, 孙浩1,2(), 呼子宇1,2, 崔慧慧3   

  1. 1.燕山大学工业计算机控制工程河北省重点实验室, 秦皇岛, 066004
    2.燕山大学电气工程学院, 秦皇岛, 066004
    3.北京航天新立科技有限公司, 北京, 100039
  • 收稿日期:2025-06-20 出版日期:2026-07-25 发布日期:2026-08-18
  • 通讯作者: 孙浩
  • 作者简介:王聪,女,1998年生,博士研究生。研究方向为柔性车间调度优化、智能优化算法设计。E-mail: congwang@stumail.ysu.edu.cn
    孙浩*(通信作者),男,1985年生,副教授、博士研究生导师。研究方向为车间调度优化、智能优化算法、深度神经网络。发表论文20余篇。E-mail: sunhao@ysu.edu.cn
  • 基金资助:
    国家重点研发计划(2022YFB3705504);国家自然科学基金(62273295);河北省自然科学基金(F2024203089);河北省重点研发计划(21310301D);河北省重点实验室项目(22567612H)

Dynamic Flexible Job Shop Scheduling Problem Considering Transportation Resource Constraints and Adaptive Competitive Reconfiguration Algorithm

WANG Cong1,2(), WEI Lixin1,2, SUN Hao1,2(), HU Ziyu1,2, CUI Huihui3   

  1. 1.Key Laboratory of Industrial Computer Control Engineering of Hebei Province,Yanshan University,Qinhuangdao,Hebei,066004
    2.School of Electrical Engineering,Yanshan University,Qinhuangdao,Hebei,066004
    3.Beijing Aerospace Xinli Technology Co. ,Ltd. ,Beijing,100039
  • Received:2025-06-20 Online:2026-07-25 Published:2026-08-18
  • Contact: SUN Hao

摘要:

针对具有运输资源的动态柔性车间调度问题设计了两阶段自适应竞争重构算法(TACRA)。初始阶段,TACRA在静态环境中运行。一旦机器故障发生,TACRA进入重调度阶段。TACRA包含可增强算法探索与开发能力的删除算子和重构算子,以及基于算子历史性能的自适应选择机制。15个测试实例中,TACRA分别在反向世代距离、超体积和适应度上取得11、15和15个最优结果。

关键词: 柔性车间调度, 多目标优化, 运输资源, 动态事件, 自适应选择

Abstract:

This paper proposes a two-stage adaptive competitive reconfiguration algorithm (TACRA) for the dynamic flexible job shop scheduling problem with transportation resources. In the initial phase, TACRA operates in a static environment; once a machine breakdown occurs, it switches to a rescheduling phase. Deletion and reconstruction operators are designed to enhance the algorithm's exploration and exploitation capabilities, and an adaptive selection mechanism is introduced based on the historical performance of these operators. Experimental results on 15 test instances show that TACRA achieves the optimal inverted generational distance in eleven cases, the optimal hypervolume in fifteen cases, and the optimal fitness metric in fifteen cases.

Key words: flexible job shop scheduling, multi-objective optimization, transportation resource, dynamic event, adaptive selection

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