Adaptive visual field and step length of chaotic artificial fish swarm algorithm

In order to solve the problem of local optimum in searching the basic artificial fish swarm, an improved artificial fish swarm algorithm with chaotic behavior is proposed. First, the Logistic chaotic sequence with uniform distribution was introduced to make the initial and search process of the fish population have the characteristics of randomness and ergodicity of chaotic behavior, and improve the global search ability. Second, the average distance between individual fish as indicators of fish species diversity, make the vision and step of artificial fish can adaptively adjust according to the variation of species diversity, avoid due to vision and step for the fixed value of early convergence speed, and the late slow convergence and easy reverberate in the search location near the point of the problem. The experimental results show that the improved artificial fish swarm algorithm can overcome the local extremum and the search result is closer to the theoretical value of the test function.