mlsanityData to 7 Oct 2026

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

arXiv 2405.01765 ↗First posted 2 May 2024cs.NE math.OCcited by 3

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Abstract (arXiv)

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.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 May 2024.

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Citing papers per year: 2025: 2; 2026: 1.

3 papers.