摘要
传统模具车间作业的调度计划具有编制复杂度高、人员经验依赖度高等特点,以作业完成总耗时最小化为目标,提出了一种优化的双种群遗传算法。基于Gen-Tsujimura-Kubota′s method编码机制,提出了一种改进后的初始种群产生方案;采用基于工件位置的交叉算子和工件对互换变异算子对种群进行交叉操作和变异操作,并保留较优个体;基于双种群理论和自适应操作,对算法模型进行优化,提高了算法的精度和搜索能力。以某模具企业的蜡模生产车间作业为例进行分析,结果表明该算法能较精确地获得车间作业调度的优质解,验证了算法的可行性和有效性。
The traditional job scheduling of mold workshop has the characteristics of high complexity and high dependence on personnel experience.An optimized double population genetic algorithm is proposed to minimize the total time spent on job completion.Based on the Gen-Tsujimura-Kubota′s method encoding mechanism,an improved initial population generation scheme is proposed.The crossover operation and mutation operation of the population are carried out by using the crossover operator based on the workpiece position and the workpiece pair exchange mutation operator,and the better individuals are retained.Based on the dual population theory and adaptive operation,the algorithm model is optimized to improve the accuracy and search ability of the algorithm.Taking the wax mold production job-shop of a mold enterprise as an example,the result shows that the algorithm can accurately obtain the high-quality solution of job-shop scheduling,which verifies the feasibility and effectiveness of the algorithm.
作者
陈逸维
刘华秋
陈洪涛
黄磊
CHEN Yiwei;LIU Huaqiu;CHEN Hongtao;HUANG Lei(New Additive Manufacturing Research Institute,Jihua Laboratory,Foshan 528000,China)
出处
《组合机床与自动化加工技术》
北大核心
2023年第8期183-187,共5页
Modular Machine Tool & Automatic Manufacturing Technique
基金
季华实验室项目(X200041TM200)。
关键词
模具
生产调度
遗传算法
双种群
mold
job-shop scheduling
genetic algorithm
double population
