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Article Details

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.

Experimental Study of Hybrid Genetic Algorithms for the Maximum Scatter Travelling Salesman Problem

Author 1: Zakir Hussain Ahmed
Author 2: Asaad Shakir Hameed
Author 3: Modhi Lafta Mutar
Author 4: Mohammed F. Alrifaie
Author 5: Mundher Mohammed Taresh

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2021.0120855

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 8, 2021.

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Abstract: We consider the maximum scatter travelling salesman problem (MSTSP), a travelling salesman problem (TSP) variant. The problem aims to maximize the shortest edge in the tour that travels each city only once in the given network. It is a very complicated NP-hard problem, and hence, exact solutions are obtainable for small sizes only. For large sizes, heuristic algorithms must be applied, and genetic algorithms (GAs) are observed to be very successful in dealing with such problems. In our study, a simple GA (SGA) and four hybrid GAs (HGAs) are proposed for the MSTSP. The SGA starts with initial population produced by sequential sampling approach that is improved by 2-opt search, and then it is tried to improve gradually the population through a proportionate selection procedure, sequential constructive crossover, and adaptive mutation. A stopping condition of maximum generation is adopted. The hybrid genetic algorithms (HGAs) include a selected local search and perturbation procedure to the proposed SGA. Each HGA uses one of three local search procedures based on insertion, inversion and swap operators directly or randomly. Experimental study has been carried out among the proposed SGA and HGAs by solving some TSPLIB asymmetric and symmetric instances of various sizes. Our computational experience reveals that the suggested HGAs are very good. Finally, our best HGA is compared with a state-of-art algorithm by solving some TSPLIB symmetric instances of many sizes. Our computational experience reveals that our best HGA is better.

Keywords: Hybrid genetic algorithm; maximum scatter travelling salesman problem; sequential constructive crossover; adaptive mutation; local search; perturbation procedure

Zakir Hussain Ahmed, Asaad Shakir Hameed, Modhi Lafta Mutar, Mohammed F. Alrifaie and Mundher Mohammed Taresh, “Experimental Study of Hybrid Genetic Algorithms for the Maximum Scatter Travelling Salesman Problem” International Journal of Advanced Computer Science and Applications(IJACSA), 12(8), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120855

@article{Ahmed2021,
title = {Experimental Study of Hybrid Genetic Algorithms for the Maximum Scatter Travelling Salesman Problem},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120855},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120855},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {8},
author = {Zakir Hussain Ahmed and Asaad Shakir Hameed and Modhi Lafta Mutar and Mohammed F. Alrifaie and Mundher Mohammed Taresh}
}


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