摘要
Petri网的优化调度求解主要采用基于状态空间的智能搜索方法,执行效率往往不高.提出基于蚁群优化的时间Petri网,通过在Petri网的变迁和进化规则中引入蚁群优化机制,改变Petri网原有的非确定性选择行为,使之具备蚁群寻优选择智能行为,克服了需要基于状态空间进行启发式搜索的缺陷,提高了调度优化的计算效率.最后应用蚁群优化时间Petri网模型,对柔性制造系统的区间Job Shop调度问题进行建模和优化求解.实验结果进一步验证了所提模型和方法的有效性.
Heuristic algorithms based on state search are usually used to solve scheduling problems of Petri nets. Suffering from the state space explosion,their executions are often not efficient for large-scale problems. This paper proposes a time Pelri net with ant colony mechanism to address this problem. We introduce pheromones and foraging rules of ants into transitions and evolu- tion rules of a time Petfi net. The proposed model can work out scheduling problems during the run of a Petri net without building reachability free. We use this model to describe and solve an interval job shop scheduling problem. The experimental results further verify the effectiveness of the proposed model.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2014年第8期1531-1537,共7页
Acta Electronica Sinica
基金
国家自然科学基金(No.61103115)
湖南省自然科学基金(No.11JJ4058
No.11JJ2037)
湖南省教育厅重点科研项目(No.11A041)
江苏省科技支撑计划(No.BE2012115)
湖南省高校科技创新团队支持计划(湘教通[2012]318-18)
关键词
调度优化
蚁群优化
时间PETRI网
柔性制造系统
scheduling optimization
ant colony optimization
time Pelri net
flexible manufacturing system
