An Improved Partheno-Genetic Algorithm With Reproduction Mechanism for the Multiple Traveling Salesperson Problem
Zijian Wang, Xi Fang, Hao Li, Hongbin Jin
Abstract
This paper considers the problem of the multiple traveling salesperson problem (MTSP) with multiple depots and closed path. We analyzed the advantages and disadvantages of Partheno-Genetic algorithm (PGA) in solving the MTSP. By integrating the reproduction mechanism in the invasive weed algorithm (IWO), we have solved the defect that the local information of individuals in the PGA population may be missing, and obtained the improved Partheno-Genetic algorithm with reproduction mechanism (RIPGA), which greatly improves the solution performance. By comparing the RIPGA with other GAs and other intelligent algorithms on a large number of traveling salesperson problem (TSP) test functions, we have well verified the solution performance of the RIPGA on the optimal solution, indicating that the algorithm can effectively avoid local convergence. At the same time, the algorithm is less affected by parameters and has good stability.