research-article

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

Authors:

Haikal El Abed,

Adel M. AlimiAuthors Info & Claims

Applied Soft Computing, Volume 25, Issue C

Pages 234 - 241

https://doi.org/10.1016/j.asoc.2014.09.031

Published: 01 December 2014 Publication History

Abstract

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.

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cover image Applied Soft Computing

Applied Soft Computing Volume 25, Issue C

December 2014

535 pages

ISSN:1568-4946

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Copyright © Elsevier B.V.

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 December 2014

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Lamperti Rde Arruda L(2023)A strategy based on Wave Swarm for the formation task inspired by the Traveling Salesman ProblemEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.106884126:PBOnline publication date: 1-Nov-2023
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