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An Effective Hybrid Metaheuristic Approach Based on the Genetic Algorithm

Authors :
Olympia Roeva
Dafina Zoteva
Gergana Roeva
Maya Ignatova
Velislava Lyubenova
Source :
Mathematics, Vol 12, Iss 23, p 3815 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

This paper presents an effective hybrid metaheuristic algorithm combining the genetic algorithm (GA) and a simple algorithm based on evolutionary computation. The evolutionary approach (EA) is applied to form the initial population of the GA, thus improving the algorithm’s performance, especially its convergence speed. To assess its effectiveness, the proposed hybrid algorithm, the EAGA, is evaluated on selected benchmark functions, as well as on a real optimisation process. The EAGA is used to identify parameters in a nonlinear system of differential equations modelling an E. coli fed-batch fermentation process. The obtained results are compared against published results from hybrid metaheuristic algorithms applied to the selected optimisation problems. The EAGA hybrid outperforms the competing algorithms due to its effective initial population generation strategy. The risk of premature convergence is reduced. Better numerical outcomes are achieved. The investigations validate the potential of the proposed hybrid metaheuristic EAGA for solving real complex nonlinear optimisation tasks.

Details

Language :
English
ISSN :
22277390
Volume :
12
Issue :
23
Database :
Directory of Open Access Journals
Journal :
Mathematics
Publication Type :
Academic Journal
Accession number :
edsdoj.687b104eb8c4862af11c35f17e5082e
Document Type :
article
Full Text :
https://doi.org/10.3390/math12233815