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A Stigmergy-Based Differential Evolution

Authors :
Valentín Osuna-Enciso
Elizabeth Guevara-Martínez
Source :
Applied Sciences, Vol 12, Iss 12, p 6093 (2022)
Publication Year :
2022
Publisher :
MDPI AG, 2022.

Abstract

Metaheuristic algorithms are techniques that have been successfully applied to solve complex optimization problems in engineering and science. Many metaheuristic approaches, such as Differential Evolution (DE), use the best individual found so far from the whole population to guide the search process. Although this approach has advantages in the algorithm’s exploitation process, it is not completely in agreement with the swarms found in nature, where communication among individuals is not centralized. This paper proposes the use of stigmergy as an inspiration to modify the original DE operators to simulate a decentralized information exchange, thus avoiding the application of a global best. The Stigmergy-based DE (SDE) approach was tested on a set of benchmark problems to compare its performance with DE. Even though the execution times of DE and SDE are very similar, our proposal has a slight advantage in most of the functions and can converge in fewer iterations in some cases, but its main feature is the capability to maintain a good convergence behavior as the dimensionality grows, so it can be a good alternative to solve complex problems.

Details

Language :
English
ISSN :
20763417
Volume :
12
Issue :
12
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.697f1d0f8bb4864ab273f9ca1c79a6b
Document Type :
article
Full Text :
https://doi.org/10.3390/app12126093