A Novel Metaheuristic Algorithm for Multiple Traveling Salesman Problem

Abstract

The Multiple Traveling Salesman Problem (MTSP) is the extension of the Traveling Salesman Problem (TSP) in which the shortest routes of m salesmen all of which start and finish in a city (depot) will be determined. In this paper, we propose new metaheuristic algorithm called Crow Swarm Optimization (CSO) algorithm for solving the multi depot multiple traveling salesmen problem (MMTSP). CSO is a metaheuristic optimization algorithm that is derived from the behavior of American Crow in finding the shortest path. In solving the MMTSP, the algorithm is observed with randomly chosen cities as depots, the fewest cities that must be visited by a salesman and the most number of cities that can be visited by a salesman. The implementation is observed with several dataset from TSPLIB. The results show that CSO is superior to some selected metaheuristics algorithms that are used to solve.