摘要
通过模仿鱼类的行为方式 ,提出了一种基于动物自治体的优化方法—人工鱼群算法 (ArtificialFish-schoolAl gorithm) ,并将其用于组合优化问题的求解 .介绍了该算法在此类问题求解中的距离、邻域等概念 ,给出了具体的实现方法 .最后以TSP问题为例对该算法进行仿真测试 .结果表明它具有快速收敛的能力 .
An optimizing method based on autonomous animats approach, artificial fish school algorithm, is presented. It is applied to solve the combinatorial optimization problem. The concepts of distance, neighborhood, center, etc., which are used in artificial fish school algorithm are introduced. Experiments of traveling salesman problems are carried out. It shows that artificial fish school algorithm has rapid convergence ability.
出处
《山东大学学报（工学版）》
CAS
2004年第5期64-67,共4页
Journal of Shandong University（Engineering Science）
基金
国家自然科学基金项目 (60 10 40 0 9)
关键词
人工鱼群算法
组合优化
寻优
TSP
artificial fish school algorithm
combinatorial optimizing
optimize
TSP
