Study of Some Recent Crossovers Effects on Speed and Accuracy of Genetic Algorithm, Using Symmetric Travelling Salesman Problem
Neural and Evolutionary Computing
2015-04-13 v1
Abstract
The Travelling Salesman Problem (TSP) is one of the most famous optimization problems. The Genetic Algorithm (GA) is one of metaheuristics that have been applied to TSP. The Crossover and mutation operators are two important elements of GA. There are many TSP solver crossover operators. In this paper, we state implementation of some recent TSP solver crossovers at first and then we use each of them in GA to solve some Symmetric TSP (STSP) instances and finally compare their effects on speed and accuracy of presented GA.
Keywords
Cite
@article{arxiv.1504.02590,
title = {Study of Some Recent Crossovers Effects on Speed and Accuracy of Genetic Algorithm, Using Symmetric Travelling Salesman Problem},
author = {Hassan Ismkhan and Kamran Zamanifar},
journal= {arXiv preprint arXiv:1504.02590},
year = {2015}
}
Comments
arXiv admin note: text overlap with arXiv:1209.5339