A local optimization algorithm based on eliminating the inclusion and intersection relations between sub tours for multi-traveling salesman problem

Abstract

Aiming at the multi traveling salesman problem(MTSP) of balancing workload, this paper proposes two local optimization operators for heuristic planning algorithm. According to the workload constraint, all the cities in the travel path are allocated to k sub tours, and a feasible solution is obtained. Then, the local optimal solution is found through the local optimization operator to optimize a single sub tour and the method of exchanging vertices between multiple sub tours. Genetic is used for global search, and there are two optimization operators in the local optimization process. Among them, eliminating the inclusion relationship operator is used to eliminate the inclusion relationship between sub tours, and the eliminating intersection relationship operator is used to avoid the intersection between different sub tours. These two operators tend to actively shorten the total length of travel, so the convergence performance is good. Data experiments show that the optimization operator in this paper has obvious optimization ability in solving similar problems of MTSP.