摘要
为了减少具有非紧密衔接工序条件下多柔性车间联合生产的总延期时间,提出了基于知识引导差分进化算法的多车间协同调度方法。基于扩展工艺树描述了产品工艺间的约束关系,并采用无向图表示不同车间之间的物流时间;考虑了工序时间约束、逻辑约束、非紧密衔接延迟约束等,建立了以总延期时间最短为目标的调度优化模型。在差分进化算法中,同时采用种群知识和个体知识引导染色体进化,提出了基于知识引导差分进化算法的求解方法。以某车间实际生产数据为基础设置实验,结果表明,与标准差分进化算法和并行协同遗传算法相比,知识引导差分进化算法调度方案的总延期时间最小,且性能最稳定,验证了该调度方法的可行性和先进性。
In order to reduce the total delay time of multi flexible workshop joint production with non⁃closely linked processes,a multi workshop collaborative scheduling method based on knowledge guided differential evolution is proposed.Based on the extended process tree,the constraint relations between product processes are described,and an undirected graph is used to represent the logistics time between different workshops.A scheduling optimization model with the goal of minimizing the total delay time is established,taking into account process time constraints,logical constraints,and non⁃closely linked delay constraints.In the differential evolution algorithm,both population knowledge and individual knowledge are used to guide the chromosome evolution,and a solution method based on knowledge guided differential evolution is proposed.Based on the actual production data of a workshop,the experiment is set up.The results show that compared with the standard differential evolution and the parallel cooperative genetic algorithm,the total delay time of the knowledge guided differential evolution scheduling scheme is the smallest,and the performance is the most stable,which verifies the feasibility and advantage of the proposed scheduling method.
作者
韦天珍
徐才胜
WEI Tianzhen;XU Caisheng(Beijing College of Finance and Commerce,Beijing 100026,China;Ottobock(China)Industry Co.,Ltd,Beijing 100013,China)
出处
《机械设计与研究》
CSCD
北大核心
2024年第1期26-30,36,共6页
Machine Design And Research
基金
2019年度北京财贸职业学院教改项目(2019WT11)。
关键词
多车间协同
联合调度
非紧密衔接工序
知识引导
差分进化算法
multi workshop collaboration
joint scheduling
non⁃closed linked processes
knowledge guidance
differential evolution algorithm
