Bionic optimization algorithm based on the MMAS and the artificial fish

According to the ant colony algorithm in many ants to find the optimal path need long time or hard to find the optimal path from the path of desultorily, and the contradiction between the shortcomings of accelerating convergence and premature stagnation phenomenon, puts forward a new bionic optimization algorithm. The main idea of the algorithm is introduced visual concepts in MMAS form artificial fish algorithm, which many of ants can more quickly find optimal path, and introduced crowded degree concepts of artificial fish algorithm to set strong crowded degree limit, which method can global optimization better and avoid the local extreme value also accelerate the speed and improve the accuracy of the algorithm. Simulation results show the effectiveness of the algorithm.