A novel global artificial fish swarm algorithm with improved chaotic search

The artificial fish swarm algorithm, it may be trapped in local optimum in the later evolution period and its search accuracy is dependent on step length which is hard to keep balance between rapidity and accuracy. Aimed at the defects of AFSA, a novel global artificial fish swarm algorithm is proposed in this paper, in which normal chaotic search on earlier stage is modified, and a differential evolution with improved chaos search was proposed to lead artificial fish into global optimum value. The experimental results show that the proposed algorithm is not only superior to traditional one but also can make the result greater.