基于拓扑结构改进的人工鱼群算法

Artificial Fish Swarm Algorithm Based on Improved Topological Structure

摘要: 人工鱼群算法是一种经典的启发式仿生算法，文章从人工鱼群算法的内部协同性出发，将自反馈模糊控制邻域结构与超立方体顶点搜索相结合应用到人工鱼群，提出基于拓扑结构改进的人工鱼群算法(TAFSA)。对高维以及多极值非线性函数的寻优问题，实验仿真结果表明，该算法具有易定位全局最优值，后期收敛速度快等优点。

Abstract: Artificial fish algorithm is a kind of classic heuristic bionic algorithm. This paper starts from the internal collaborative of artificial fish algorithm, and the feedback fuzzy control neighborhood structure combined with super cube vertices searching to the artificial group is applied, then the improved artificial fish algorithm based on the topological structure (TAFSA) is proposed. For high-dimensional and more extreme nonlinear function optimization problems, the experimental simulation results show that the algorithm is easy to locate the global optimal value and has the fast convergence speed.