求解PFSP的双种群协同学习算法

发布时间：2018-03-21 15:01

  本文选题：协同学习　切入点：置换流水车间调度　出处：《控制与决策》2017年01期 　论文类型：期刊论文

【摘要】：在人工蜜蜂群算法的基础上,提出一种双种群协同学习算法.该算法根据个体适应度高低把蜜蜂群划分为两个子群,并重新定义子群的学习交流机制.在10个常用的基准测试函数上与其他4个常用的群体智能算法进行比较,比较结果表明,所提出算法的性能有明显改进.采用双种群协同学习算法求解置换流水车间调度问题,在一些著名的中大规模测试问题包括21个Reeves实例和40个Taillard实例上进行测试,结果表明,所提出的算法优于其他算法,能有效解决置换流水车间调度问题.
[Abstract]:Based on the artificial bee colony algorithm, a two-population cooperative learning algorithm is proposed, which divides the bee colony into two subgroups according to the individual fitness. The learning communication mechanism of the subgroup is redefined and compared with the other four swarm intelligence algorithms on 10 common benchmark functions. The results show that, The performance of the proposed algorithm is improved obviously. A two-population cooperative learning algorithm is used to solve the permutation income job-shop scheduling problem. The results show that the proposed algorithm is tested on 21 Reeves instances and 40 Taillard instances in some famous medium-large-scale test problems. The proposed algorithm is superior to other algorithms and can effectively solve the displacement income job shop scheduling problem.
【作者单位】： 中国科学院沈阳自动化研究所;中国科学院大学;
【基金】：国家杰出青年科学基金项目(61174164,51205389) 辽宁省自然科学基金项目(2015020163)
【分类号】：TP181;TB497
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本文编号：1644364