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

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arxiv 2405.01765 v3 pith:HSFWSVGO submitted 2024-05-02 cs.NE math.OC

Mariana A. Londe , Luciana S. Pessoa , Cartlos E. Andrade , Mauricio G.C. Resende This is my paper · ORCID
classification cs.NEmath.OC
keywords applicationsbiasedbrkgageneticreviewalgorithmsmetaheuristicproblems
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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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