A comparative study of the improvement of performance using a PSO modified by ACO applied to TSP

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86092830" target="_blank" >RIV/61989100:27240/14:86092830 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.asoc.2014.09.031" target="_blank" >http://dx.doi.org/10.1016/j.asoc.2014.09.031</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.asoc.2014.09.031" target="_blank" >10.1016/j.asoc.2014.09.031</a>

Result language
angličtina
Original language name
A comparative study of the improvement of performance using a PSO modified by ACO applied to TSP
Original language description
Swarm-inspired optimization has become very popular in recent years. Particle swarm optimization (PSO) and Ant colony optimization (ACO) algorithms have attracted the interest of researchers due to their simplicity, effectiveness and efficiency in solving complex optimization problems. Both ACO and PSO were successfully applied for solving the traveling salesman problem (TSP). Performance of the conventional PSO algorithm for small problems with moderate dimensions and search space is very satisfactory.As the search, space gets more complex, conventional approaches tend to offer poor solutions. This paper presents a novel approach by introducing a PSO, which is modified by the ACO algorithm to improve the performance. The new hybrid method (PSO-ACO) is validated using the TSP benchmarks and the empirical results considering the completion time and the best length, illustrate that the proposed method is efficient. (C) 2014 Elsevier B.V. All rights reserved.
Czech name
—
Czech description
—

Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
—

Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)