The Routing Optimization Based on Improved Artificial Fish Swarm Algorithm

Abstract

A novel algorithm named artificial fish swarm algorithm (AFSA) is discussed to solve the problem of routing optimization in computer communication networks. An improved AFSA (IAFSA) with the taboo table and a new parameter is proposed to increase the global optimum capability and the neighborhood search ability of AFSA. A mathematical model of routing optimization based on the minimal time delay is established. By description and analysis of AFSA, its principle and convergence capability are given. The experiment demonstrates that IAFSA has better capability and rapidity to search the global optimum. Summarization of AFSA's characteristics and ideas for improvement are presented according to the comparative result between AFSA and genetic algorithm