%0 Journal Article
%T Analyzing the Performance of Mutation Operators to Solve the Traveling Salesman Problem
%A Otman Abdoun
%A Chakir Tajani
%A Jaafar Abouchabaka
%J International Journal of Emerging Sciences
%D 2012
%I Islamia University of Bahawalpur
%X The genetic algorithm includes some parameters that should be adjusted, so as to get reliable results. Choosing a representation of the problem addressed, an initial population, a method of selection, a crossover operator, mutation operator, the probabilities of crossover and mutation, and the insertion method creates a variant of genetic algorithms. Our work is part of the answer to this perspective to find a solution for this combinatorial problem. What are the best parameters to select for a genetic algorithm that creates a variety efficient to solve the Traveling Salesman Problem (TSP)? In this paper, we present a comparative analysis of different mutation operators, surrounded by a dilated discussion that justifying the relevance of genetic operators chosen to solving the TSP problem.
%K Genetic Algorithm
%K TSP
%K Mutation Operator
%K Probability of mutation
%U http://ijes.info/2/1/42542105.pdf