Extending Genetic Algorithms with Biological Life-Cycle Dynamics

Autor: J. C. Felix-Saul, Mario García-Valdez, Juan J. Merelo Guervós, Oscar Castillo
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Biomimetics, Vol 9, Iss 8, p 476 (2024)
Druh dokumentu: article
ISSN: 2313-7673
DOI: 10.3390/biomimetics9080476
Popis: In this paper, we aim to enhance genetic algorithms (GAs) by integrating a dynamic model based on biological life cycles. This study addresses the challenge of maintaining diversity and adaptability in GAs by incorporating stages of birth, growth, reproduction, and death into the algorithm’s framework. We consider an asynchronous execution of life cycle stages to individuals in the population, ensuring a steady-state evolution that preserves high-quality solutions while maintaining diversity. Experimental results demonstrate that the proposed extension outperforms traditional GAs and is as good or better than other well-known and well established algorithms like PSO and EvoSpace in various benchmark problems, particularly regarding convergence speed and solution qu/ality. The study concludes that incorporating biological life-cycle dynamics into GAs enhances their robustness and efficiency, offering a promising direction for future research in evolutionary computation.
Databáze: Directory of Open Access Journals
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