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arXiv · 2405.01765

Early years of Biased Random-Key Genetic Algorithms: A systematic review

Mariana A. Londe·Luciana S. Pessoa·Cartlos E. Andrade·Mauricio G. C. Resende
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Abstract

This paper presents a systematic literature review and bibliometric analysis focusing on Biased Random-Key Genetic Algorithms (BRKGA). BRKGA is a metaheuristic framework that uses random-key-based chromosomes with biased, uniform, and elitist mating strategies alongside a genetic algorithm. This review encompasses around~250 papers, covering a diverse array of applications ranging from classical combinatorial optimization problems to real-world industrial scenarios, and even non-traditional applications like hyperparameter tuning in machine learning and scenario generation for two-stage problems. In summary, this study offers a comprehensive examination of the BRKGA metaheuristic and its various applications, shedding light on key areas for future research.

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Mariana A. Londe, Luciana S. Pessoa, Cartlos E. Andrade, Mauricio G. C. Resende. 2024-05-02. Early years of Biased Random-Key Genetic Algorithms: A systematic review. https://doi.org/10.1007/s10898-024-01446-5

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