太原理工大学学报2024，Vol.55Issue(4)：603-611,9.DOI:10.16355/j.tyut.1007-9432.20230652
基于改进灰狼算法的柔性作业车间重调度问题研究
Research on Flexible Job Shop Rescheduling Problem Based on Improved Grey Wolf Algorithm
摘要
Abstract
[Purposes]In actual processing of factories,the varying health status of each ma-chine can cause machine failures and subsequently affect the processing and construction time.This article focuses on the problem of flexible job shops with machine disturbances.In order to reduce the impact of machine failures on production planning,a rescheduling model for machine disturbances and breakpoint finding is proposed.A mathematical model is constructed with the optimization objectives of the minimum processing time and the minimum total delay time.[Methods]The improved grey wolf optimization algorithm(GWO-GA)is proposed as a global optimization search algorithm for solution.In order to improve the convergence rate of its gray wolf algorithm,the work piece coding iteration is introduced with an adaptive operator be added,and the POX crossover of genetic algorithm is used to iterate the machine coding.[Findings]The validation is conducted on the solid wood workshop data of piano manufacturing enterprises,and the results show that compared with genetic algorithm,NSGA,and PSO-GA,the improved grey wolf algorithm has advantages of high efficiency,good accuracy,and good practical value in sol-ving this scheduling problem.关键词
柔性作业车间/灰狼算法/机器扰动/重调度Key words
flexible workshop/grey wolf algorithm/machine disturbance/reschedule分类
机械制造引用本文复制引用
李浩平,杜昕毅,朱成彪,金朱鸿,陈心怡,于波涛,李景瑞,安宇婷..基于改进灰狼算法的柔性作业车间重调度问题研究[J].太原理工大学学报,2024,55(4):603-611,9.基金项目
国家重点研发计划资助项目(2018YFB1700801) （2018YFB1700801）
湖北省水电工程施工与管理重点实验室(三峡大学)开放基金项目(2020KSD15) （三峡大学）
