An Improved Chicken Swarm Optimization for TSP

Abstract

Chicken Swarm Optimization is a kind of swarm intelligence algorithm which simulates the hierarchy and behavior of chicken swarm. For Traveling Salesman Problem (TSP) of combinatorial optimization, a path optimization scheme based on improved chicken swarm optimization is proposed. Combining the strategy of exchange operator and exchange sequence, the chicken swarm optimization for solving continuous space problem is mapped to discrete path optimization. At the same time, in order to improve the moving ability of chicken swarm, a self-exploration strategy is added to the chicken swarm and simulated annealing operator is combined to improve the global search performance of the algorithm and prevent the chickens from falling into local optimum due to over quick convergence. Finally, through data testing and simulation of TSPLIB standard library, the experimental results show that the improved chicken swarm optimization has better optimization ability than other similar algorithms.