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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.
Based on the artificial bee colony algorithm, this paper proposes a two-species collaborative learning algorithm, which divides the honeybee population into two subgroups according to individual fitness level and redefines the learning exchange mechanism of subgroups.On the 10 commonly used benchmark The test function is compared with the other four commonly used swarm intelligence algorithms, and the comparison results show that the performance of the proposed algorithm has been significantly improved.Double-species cooperative learning algorithm is used to solve the scheduling problem of displacement flow shop, and in some famous large-scale test problems Including 21 Reeves instances and 40 Taillard instances. The experimental results show that the proposed algorithm is superior to other algorithms and can effectively solve the scheduling problem of displacement flow shop.