基于Petri网和改进遗传算法的多资源调度问题
Multi-resource scheduling problem based on Petri net and improved genetic algorithm
高慕云 1李榜华 2马浩亮 2张福礼 2贺可太1
作者信息
- 1. 北京科技大学机械工程学院,北京 100083
- 2. 北京航天控制仪器研究所精密装配车间,北京 100854
- 折叠
摘要
针对混流装配线工序加工资源需求多样、工艺复杂、装配工期长等问题,采用Petri网和改进遗传算法对该问题进行优化求解.建立混流装配线赋时库所Petri网(timed place Petri net,TPPN)调度模型,基于模型激发序列,采用基于工序的编码方式进行染色体编码;采用精英保留策略选择优异个体,改进遗传算法的交叉、变异操作,用改进后的遗传算法求解混流装配线调度问题.通过对比案例及实例数据计算结果验证了方案的有效性.
Abstract
Aiming at the problems of diverse processing resource requirements,complex process and long production period on mixed-flow assembly line,the Petri net and improved genetic algorithm were used to optimize the solution of the problem.According to the process flow of the mixed assembly line,the timed place Petri net(TPPN)scheduling model of the mixed assembly line was established.Based on the excitation sequence of the Petri Net model,the chromosome coding method based on the process was used.The elite retention strategy was used to select outstanding individuals,and the crossover and mutation operations of genetic algorithm were improved.The improved genetic algorithm was used to solve the mixed-flow assembly line scheduling problem.The effectiveness of the scheme is verified by comparing the calculation results of cases and example data.
关键词
混流装配线/多资源调度/赋时库所佩特里网/改进遗传算法/交叉策略/变异策略/调度规则Key words
mixed-flow assembly line/multi-resource scheduling/timed place Petri net/improved genetic algorithm/crossover strategy/mutation strategy/scheduling rules引用本文复制引用
基金项目
国防基础科研重大项目(JCKY2018203A002)
出版年
2024
NETL
NSTL
万方数据