摘要
针对模具多项目执行过程中任务拖期导致的调度计划变更,提出了一种启发式动态调度算法。利用改进的微粒群算法构建一个加权工期之和最小的初始调度计划,并基于关键链管理方法对初始调度计划进行合理地缓冲设置。建立了以调度计划变更费用最小为优化目标的启发式动态调度模型,并用改进的微粒群算法进行求解。通过仿真计算分析了算法的可行性与可靠性,并与标准的微粒群算法进行了比较。
A heuristic dynamic scheduling algorithm was proposed to repair multiple mould and die projects baseline scheduling which suffered from multiple tasks taking longer time than planning during projects execution.Firstly,a baseline scheduling minimizing weighted sum duration of projects was established with improved Particle Swarm Optimization（PSO）and was improved by setting time buffers based on critical chain management method.Then,a heuristic dynamic scheduling model with optimization object of minimizing disruptions cost was constructed,and the improved PSO was used to solve it.Finally,feasibility and reliability of the improved PSO were analyzed by simulations,and it was compared to normal PSO.
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2011年第3期622-629,共8页
Computer Integrated Manufacturing Systems
基金
国家863计划资助项目(2006AA04Z132)
国家自然科学基金资助项目(50875051
50675039)
广东工业大学青年基金资助项目(20062014)~~
关键词
模具
多项目调度
动态调度
关键链
微粒群算法
启发式算法
mould and die
multiple projects scheduling
dynamic scheduling
critical chain
particle swarm optimization algorithm
heuristic algorithms
