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Comparison between ant colony and genetic algorithm using traveling salesman problem

Abduljabbar, Zaid Ammen and Khalefa, Mustafa S. and A. Jabar, Marzanah (2013) Comparison between ant colony and genetic algorithm using traveling salesman problem. International Journal of Soft Computing, 8 (3). pp. 171-174. ISSN 1816-9503

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Abstract

The Travelling Salesman Problem (TSP) is a complex problem in combinatorial optimization. The aim of this study is compare the effect of using two distributed algorithm which are ant colony as a Swarm intelligence algorithm and genetic algorithm. In ant colony algorithm each individual ant constructs a part of the solution using an artificial pheromone which reflects its experience accumulated while solving the problem and heuristic information dependent on the problem. The results of comparison show that ant colony is high efficient than genetic algorithm and it requires less computational cost and generally only a few lines of code.

Item Type:Article
Keyword:Ant colony; Genetic algorithm; Combinatorial optimization; Distributed algorithm
Faculty or Institute:Faculty of Computer Science and Information Technology
Publisher:Medwell Publishing
ID Code:30686
Deposited By: Nida Hidayati Ghazali
Deposited On:02 Jun 2014 10:42
Last Modified:30 Jun 2016 14:31

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