基于人工鱼群算法的多播树演化寻优

Evolving multicast tree based artificial fish swarm algorithm

提出了一种双域模型人工鱼群算法。算法采用前驱节点指向的编码方法形成多播树表示人工鱼,将搜索空间分为可行域和非可行域。分别赋予可行域和非可行域的人工鱼不同的游动目标,设计行为算子自适应地执行4种人工鱼行为。数值实验结果表明,提出的算法可以有效利用非可行个体,具有较好的求解时延约束最小代价多播树的性能。

An artificial fish swarm algorithm with two regions model was proposed.The algorithm used a multicast tree formed by the predecessor orientation method to represent an artificial fish,and divided the search space into feasible re-gion and infeasible region.The artificial fishes in the feasible region and the infeasible region were given different mov-ing objectives,respectively.The behavior operator was designed to adaptively implement four behaviors of artificial fish.Experimental results show that the proposed algorithm can effectively make use of the infeasible individuals and per-forms better in searching least-cost multicast tree with delay constraint.