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.
%0 Journal Article
%1 IJACSA.2011.020104
%A Adewole Philip Akinwale Adio Taofiki, Otunbanowo Kehinde
%D 2011
%J International Journal of Advanced Computer Science and Applications(IJACSA)
%K Algorithm Generation, Mutation Population, Problem,Genetic Salesman Travelling rate,
%N 1
%T A Genetic Algorithm for Solving Travelling Salesman Problem
%U http://ijacsa.thesai.org/
%V 2
%X 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.
@article{IJACSA.2011.020104,
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.},
added-at = {2014-02-21T08:00:08.000+0100},
author = {{Adewole Philip Akinwale Adio Taofiki}, Otunbanowo Kehinde},
biburl = {https://www.bibsonomy.org/bibtex/2eb3fafdb651f37aee16928edcfdbed6e/thesaiorg},
interhash = {c0be4f477500ddbc42c0ac37f53184f9},
intrahash = {eb3fafdb651f37aee16928edcfdbed6e},
journal = {International Journal of Advanced Computer Science and Applications(IJACSA)},
keywords = {Algorithm Generation, Mutation Population, Problem,Genetic Salesman Travelling rate,},
number = 1,
timestamp = {2014-02-21T08:00:08.000+0100},
title = {{A Genetic Algorithm for Solving Travelling Salesman Problem}},
url = {http://ijacsa.thesai.org/},
volume = 2,
year = 2011
}