A discrete chicken swarm optimization for traveling salesman problem
Yuanjie Liu, Qiang Liu, Zhi Li Tang · Journal of Physics Conference Series · 2021
Abstract Traveling Salesman Problem (TSP) is a typical combinatorial optimization problem, and it is a NP-hard problem. The total number of routes increases exponentially with the number of cities, so it is great significance to design an effective algorithm to find the optimal solution accurately. Chicken Swarm Optimization (CSO) is a new intelligent optimization algorithm, which is mainly proposed for continuous problems. It has the advantages of fast convergence speed and high convergence accuracy. This paper proposed a Discrete Chicken Swarm Optimization (DCSO) for TSP. The CSO is discretized by introducing the methods of swap, order crossover and reverse order mutation, where the search space of the solution is enlarged, and the diversity of the solution is increased. The typical TSP models are simulated and compared with the Basic Ant Colony Optimization and Genetic Algorithm to verify the feasibility of the presented method.