2026-06-01T22:07:58Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/368482026-02-03T11:31:00Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Harada, Tomohiro
author
Alba-Torres, Enrique
2025-01-23T13:17:08Z
2025-01-23T13:17:08Z
2020-08-20
Tomohiro Harada and Enrique Alba. 2020. Parallel Genetic Algorithms: A Useful Survey. ACM Comput. Surv. 53, 4, Article 86 (August 2020), 39 pages. https://doi.org/10.1145/3400031
https://hdl.handle.net/10630/36848
10.1145/3400031
In this article, we encompass an analysis of the recent advances in parallel genetic algorithms (PGAs). We have selected these algorithms because of the deep interest in many research fields for techniques that can face complex applications where running times and other computational resources are greedily consumed by present solvers, and PGAs act then as efficient procedures that fully use modern computational platforms at the same time that allow the resolution of cutting edge open problems. We have faced this survey on PGAs with the aim of helping newcomers or busy researchers who want to have a wide vision on the field. Then, we discuss the most well-known models and their implementations from a recent (last six years) and useful point of view: we discuss on highly cited articles, keywords, the venues where they can be found, a very comprehensive (and new) taxonomy covering different research domains involved in PGAs, and a set of recent applications. We also introduce a new vision on open challenges, and try to give hints that guide practitioners and specialized researchers. Our conclusion is that there are many advantages to using these techniques, and lots of potential interactions to other evolutionary algorithms, as well as we contribute to creating a body of knowledge in PGAs by summarizing them in a structured way, so that the reader can find this article useful
for practical research, graduate teaching, and as a pedagogical guide to this exciting domain.
eng
Algoritmos genéticos
Optimización combinatoria
Parallel genetic algorithms: a useful survey
journal article
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URL
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File
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921e79890445d807f30ed9cce29e200f
2646605
application/pdf
2020 ACM Computing Surveys - Parallel Genetic Algorithms (preprint).pdf