摘要
以柔性作业车间实际制造过程为对象,考虑工件在加工机器间运输时间对调度结果的影响,建立了以最大完工时间最小、最小碳排放量、最小机器负载为优化目标的柔性作业车间调度问题模型。提出了改进粒子群算法,该算法在种群基因段前、后两部分分别采用不同的交叉方式,避免算法陷入局部最优解,融合NSGA-II中非支配排序策略来解决多目标问题。最后,以某柔性作业车间为对象,与传统粒子群和NSGAII算法进行对比,证明了算法的可行性和优越性。
This paper describes the flexible job shop scheduling problem model aiming to achieve the optimum objectives,in terms of maximum completion time,minimum carbon emission and minimum machine load.An improved particle swarm optimization algorithm is proposed.This algorithm adopts different crossover methods to avoid the local optimal solution.NSGA-II non-dominant sorting strategy has been utilized in the algorithm to solve the multi-objective problem.Finally,the feasibility and superiority of the developed algorithm are proved by comparing with the generated results from traditional particle swarm optimization and NSGA-II algorithm.
作者
李香怡
何星月
王磊
唐红涛
LI Xiangyi;HE Xingyue;WANG Lei;TANG Hongtao(School of Mechanical and Electronic Engineering,Wuhan University of Technology,Wuhan 430070,China;Wuhan No.15 High School,Wuhan 430000,China)
关键词
运输时间
粒子群算法
柔性作业车间调度
transport time
particle swarm optimization
flexible job shop scheduling
作者简介
李香怡(1997-),女,湖北襄阳人,武汉理工大学机电工程学院硕士研究生.
