求解多目标柔性作业车间调度问题的混合自适应差分进化算法  

Hybrid adaptive differential evolution for multi-objective flexible job shop scheduling problem

作　　者：陈永灿 刘宇 周艳平[1] CHEN Yongcan;LIU Yu;ZHOU Yanping(School of Information Science&Technology,Qingdao University of Science and Technology,Qingdao 266061,CHN)

机构地区：[1]青岛科技大学信息科学技术学院,山东青岛266061

出　　处：《制造技术与机床》2023年第12期171-177,共7页Manufacturing Technology & Machine Tool

摘　　要：针对多目标柔性作业车间调度问题,文章提出一种混合自适应差分进化算法,将最小化最大加工时间、最小化机器最大负荷和最小化总机器负荷3个目标函数进行优化,结合使用Pareto支配关系的精英选择策略和模拟退火算法,提高了算法性能。最后通过仿真实验表明了所提算法在解决多目标柔性作业车间调度问题的有效性。For multi-objective flexible job shop scheduling problem,this paper proposes a hybrid adaptive Differential evolution,which optimizes the three objective functions of minimizing the maximum processing time,minimizing the maximum machine load,and minimizing the total machine load.Combining the elite selection strategy using Pareto dominance relationship and simulated annealing algorithm,the algorithm performance is improved.Finally,simulation experiments were conducted to demonstrate the effectiveness of the proposed algorithm in solving multi-objective flexible job shop scheduling problems.

关 键 词：柔性作业车间调度 多目标优化 差分进化算法 PARETO支配 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]