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

• URL: http://arxiv.org/abs/2405.01765v3
• Date: Thu, 23 May 2024 13:47:57 GMT
• Title: Early years of Biased Random-Key Genetic Algorithms: A systematic review
• Authors: Mariana A. Londe, Luciana S. Pessoa, Cartlos E. Andrade, Mauricio G. C. Resende,
• Abstract summary: 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.
• Score: 2.249916681499244
• License: http://creativecommons.org/licenses/by/4.0/
• 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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