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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 6, 2020.
Abstract: The maximum scatter traveling salesman problem (MSTSP), a variation of the famous travelling salesman problem (TSP), is considered here for our study. The aim of problem is to maximize the minimum edge in a salesman’s tour that visits each city exactly once in a network. It is proved be NP-hard problem and considered to be very difficult problem. To solve this kind of problems efficiently, one must use heuristic/metaheuristic algorithms, and genetic algorithm (GA) is one of them. Out of three operators in GAs, crossover is the most important operator. So, we consider eight crossover operators in GAs for solving the MSTSP. These operators have originally been designed for the TSP which can also be applied on the MSTSP after some modifications. The crossover operators are first illustrated manually through an example and then executed on some well-known TSPLIB instances of different types and sizes. The obtained comparative study clearly demonstrates the usefulness of the sequential constructive crossover operator for the MSTSP. Finally, a relative ranking of the crossover operators is reported.
Zakir Hussain Ahmed, “A Comparative Study of Eight Crossover Operators for the Maximum Scatter Travelling Salesman Problem” International Journal of Advanced Computer Science and Applications(IJACSA), 11(6), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110642
@article{Ahmed2020,
title = {A Comparative Study of Eight Crossover Operators for the Maximum Scatter Travelling Salesman Problem},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110642},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110642},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {6},
author = {Zakir Hussain Ahmed}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.