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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.
A Genetic Algorithm for Solving Travelling Salesman Problem
Digital Object Identifier (DOI) : 10.14569/IJACSA.2011.020104
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 2 Issue 1, 2011.
Abstract: In this paper we present a Genetic Algorithm for solving the Travelling Salesman problem (TSP). Genetic Algorithm which is a very good local search algorithm is employed to solve the TSP by generating a preset number of random tours and then improving the population until a stop condition is satisfied and the best chromosome which is a tour is returned as the solution. Analysis of the algorithmic parameters (Population, Mutation Rate and Cut Length) was done so as to know how to tune the algorithm for various problem instances.
Keywords: Genetic Algorithm, Generation, Mutation rate, Population, Travelling Salesman Problem
Adewole Philip, Akinwale Adio Taofiki and Otunbanowo Kehinde, “A Genetic Algorithm for Solving Travelling Salesman Problem ” International Journal of Advanced Computer Science and Applications(IJACSA), 2(1), 2011. http://dx.doi.org/10.14569/IJACSA.2011.020104
@article{Philip2011,
title = {A Genetic Algorithm for Solving Travelling Salesman Problem
},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2011.020104},
url = {http://dx.doi.org/10.14569/IJACSA.2011.020104},
year = {2011},
publisher = {The Science and Information Organization},
volume = {2},
number = {1},
author = {Adewole Philip and Akinwale Adio Taofiki and Otunbanowo Kehinde}
}
