ABSTRACT
Artificial fish swarm algorithm (AFSA) is a population-based evolutionary computing (EC) technique that is inspired by the social behavior of fish schooling and swarm intelligence (SI). AFSA, with its artificial fish (AF) concept, was proposed by Dr. Li Xiao-Lei in 2002 [1]. AF adopts information by sense organs and performs stimulant reaction by controlling the tail and fin. The AFSA is a robust stochastic technique in solving optimization problems based on the movement and intelligence of swarms in the food-finding process. Swarms have much explorative capability and noncentralized decision making. The three main principles developed in AFSA are the fish behaviors in food searching, swarming, and following.
