The Cluster Crossover Operation for The Symmetric Travelling Salesman Problem

This paper proposed the new algorithm intended to solve a specific real-world problem, the symmetric travelling salesman problem. The proposed algorithm is based on the concept of the galaxy based search algorithm (GbSA) and embedded the new ideas called the clockwise search process and the cluster crossover operation. In the first step, the nearest neighbor algorithm introduces to generate the initial population. Then, the tabu list local search is employed to search for the new solution in surrounding areas of the initial population in the second step. The clockwise search process and the cluster crossover operation are employed to create more diversity of the new solution. Then, the final step, the hill climbing local search is utilized to increase the local search capabilities. The experiments with the standard benchmark test sets show that the proposed algorithm can be found the best average percentage deviation from the lower bound.