Genetic Algorithms for the Multiple Travelling Salesman Problem

We consider the multiple travelling salesman Problem (MTSP) that is one of the generalization of the travelling salesman problem (TSP). For solving this problem genetic algorithms (GAs) based on numerous crossover operators have been described in the literature. Choosing effective crossover operator can give effective GA. Generally, the crossover operators that are developed for the TSP are applied to the MTSP. We propose to develop simple and effective GAs using sequential constructive crossover (SCX), adaptive SCX, greedy SCX, reverse greedy SCX and comprehensive SCX for solving the MTSP. The effectiveness of the crossover operators is demonstrated by comparing among them and with another crossover operator on some instances from TSPLIB of various sizes with different number of salesmen. The experimental study shows the promising results by the crossover operators, especially CSCX, for the MTSP.

@article{Al-Furhud2020,
  title     = {Genetic Algorithms for the Multiple Travelling Salesman Problem},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {11},
  number    = {7},
  year      = {2020},
  publisher = {The Science and Information Organization},
  author    = {Maha Ata Al-Furhud and Zakir Hussain Ahmed},
  doi       = {10.14569/IJACSA.2020.0110768},
  url       = {https://doi.org/10.14569/IJACSA.2020.0110768}
}