求解最短路径问题的改进人工鱼群算法研究

Research on improved artificial fish swarm algorithm to solve the shortest path problem

最短路径问题是交通网络分析中的一个重要问题,它是组合优化领域内经典问题之一。文中分析基本人工鱼群算法模型,指出其在求解交通路网最优路径问题中的不足,对人工鱼初始化和行为进行了改进。仿真实验表明,改进的人工鱼群算法(AFSA)具有更快的全局收敛速度,能有效地克服"早熟"收敛,是一种有效解决最短路径问题的寻优模式。

The shortest path problem is an important problem in traffic network analysis. It is one of the classical problems in combinatorial optimization field. This paper analyzed the basic artificial fish swarm algorithm model, pointed out its insufficiency in solving the traffic network optimal path problem, and improved the initialization and behaviors of the artificial fish swarm algorithm. The simulation results show that the improved AFSA has the faster global convergence speed. It can effectively overcome the ＂premature＂ convergence. It is an effective optimization model to solve the shortest path problem.