A Novel Evolutionary Algorithm for Multiple Traveling Salesman Problem Containing Targets with Multiple Visits

With the great development of economic globalization and the logistics industry, various scenarios in daily life require multiple visits to certain targets derived from the multiple traveling salesman problem. However, the research on multiple traveling salesman problems containing targets with multiple visits has not obtained enough attention, and traditional optimization algorithms have a challenge of low efficiency in solving this problem. Therefore, we propose a novel evolutionary algorithm to make it effective in solving this problem, with two novel designs on the path planning strategy and crossover operation. Finally, on the new test set generated from the classic traveling salesman problem test set Att48, we compare the proposed evolutionary algorithm with the greedy algorithm, verifying the effectiveness of the proposed evolutionary algorithm.