Improving Metaheuristic Algorithm Design Through Inequality and Diversity Analysis: A Novel Multi-Population Differential Evolution

In evolutionary algorithms and metaheuristics, defining when applying a specific operator is important. Besides, in complex optimization problems, multiple populations can be used to explore the search space simultaneously. However, one of the main problems is extracting information from the populat...

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Veröffentlicht in:2023 IEEE Symposium Series on Computational Intelligence (SSCI) S. 1547 - 1552
Hauptverfasser: Ramos-Michel, Alfonso, Navarro, Mario A., Oliva, Diego, Morales-Castaneda, Bernardo, Casas-Ordaz, Angel, Valdivia, Arturo, Rodriguez-Esparza, Erick, Jalaleddin Mousavirad, Seyed
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 05.12.2023
Schlagworte:
Differential evolution
Diversity
Evolutionary computation
Gini index
Heuristic algorithms
K-means
Metaheuristics
Multi-population
Ranking (statistics)
Search problems
Sociology
Space exploration
ISBN:9781665430654, 1665430656
ISSN:2472-8322
Online-Zugang:Volltext
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Zusammenfassung:In evolutionary algorithms and metaheuristics, defining when applying a specific operator is important. Besides, in complex optimization problems, multiple populations can be used to explore the search space simultaneously. However, one of the main problems is extracting information from the populations and using it to evolve the solutions. This article presents the inequality-based multi-population differential evo-lution (IMDE). This algorithm uses the K-means to generate subpopulations (settlements). Two variables are extracted from the settlements, the diversity and the Gini index, which measure the solutions' distribution and the solutions' inequality regarding fitness. The Gini index and the diversity are used in the IMDE to dynamically modify the scalation factor and the crossover rate. Experiments over a set of benchmark functions with different degrees of complexity validate the performance of the IMDE. Besides comparisons, statistical and ranking average validate the search capabilities of the IMDE.
ISBN:9781665430654
1665430656
ISSN:2472-8322
DOI:10.1109/SSCI52147.2023.10371862