改进遗传算法求解含单转运系统车间调度问题  

Improved genetic algorithm for flowshop scheduling problem with single-transporter systems

作　　者：轩华 武怡璇 王薛苑 XUAN Hua;WU Yi-xuan;WANG Xue-yuan(School of Management,Zhengzhou University,Zhengzhou 450001,China)

机构地区：[1]郑州大学管理学院,河南郑州450001

出　　处：《计算机工程与设计》2025年第1期249-256,共8页Computer Engineering and Design

基　　金：河南省科技攻关计划基金项目(232102321093、232102321026);国家自然科学基金项目(U1804151);2023年河南省哲学社会科学规划基金项目(2023BJJ085)。

摘　　要：研究单转运系统分布式置换流水线调度问题,任一工厂内连续两台机器间有一台运输能力有限的转运机器人。基于此,提出一种多策略融合改进遗传算法以最小化最大完工时间。引入Logistic-tent混沌搜索、基于K-均值聚类的NEH算法和修正NEH算法以改善初始工厂加工序列群的质量,运用结合均匀多点交叉和互换变异的自适应交叉变异算子或工厂内/间交叉变异算子进行解的调整,设计一种基于主工厂的邻域搜索(key-factory-based local search,KFLS)和半初始化策略进行再次优化。仿真结果表明了该算法的有效性。A distributed permutation flowline problem of single-transporter systems was studied where an available transport robot with limited transport capacity between two continuous machines exist in any factory.Based on this,the multi-strategy fusion improved genetic algorithm was proposed to minimize the maximum completion time.The Logistic-tent chaotic search,Nawaz-Enscore-Ham(NEH)algorithm based on K-means clustering and the modified NEH algorithm were introduced to improve the quality of the initial factory processing sequence group.The self-adaptive crossover and mutation operators based on uniform multi-point crossover and exchange mutation or inter/external-factory crossover and mutation operators were applied to adjust solutions.The key-factory-based local search and semi-initialization strategy were designed for re-optimization.Simulation results show that the algorithm is effective.

关 键 词：分布式车间 置换流水线 转运机器人 多策略融合 改进遗传算法 运输时间 等待时间 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]