Journal of System Simulation ›› 2019, Vol. 31 ›› Issue (1): 36-42.doi: 10.16182/j.issn1004731x.joss.17-0046

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Multi-chromosome Genetic Algorithm for Multiple Traveling Salesman Problem

Ye Duofu, Liu Gang, He Bing   

  1. Rocket Force University of Engineering, Xi’an 710025, China
  • Received:2017-01-10 Revised:2017-05-04 Online:2019-01-08 Published:2019-04-16

Abstract: A multi-traveling salesman model with time window is established, and two objective functions for the number of traveling salesmen and the sum of travel time are designed. A multi - chromosome coding method is designed to develop complex mutation operator tree, which overcomes the problem of large searching space of traditional genetic algorithms. The performances of algorithms are compared by simulation, and the simulation results show that the genetic algorithm with complex multi-chromosome mutation tree can balance the two objective functions of the number of TSP and total travel time well, improve the algorithm of travel speed, and reduce the total travel time by 15.8%.

Key words: multi-traveling salesman problem, time window, coding, multi-chromosome genetic algorithm, mutation operator tree

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