A Novel Learning-Based Binarization Scheme Selector for Swarm Algorithms Solving Combinatorial Problems

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dc.contributor.authorLemus-Romani, Jose
dc.contributor.authorBecerra-Rozas, Marcelo
dc.contributor.authorCrawford, Broderick
dc.contributor.authorSoto, Ricardo
dc.contributor.authorCisternas-Caneo, Felipe
dc.contributor.authorVega, Emanuel
dc.contributor.authorCastillo, Mauricio
dc.contributor.authorTapia, Diego
dc.contributor.authorAstorga, Gino
dc.contributor.authorPalma, Wenceslao
dc.contributor.authorCastro, Carlos
dc.contributor.authorGarcia, Jose
dc.date.accessioned2025-01-20T22:02:15Z
dc.date.available2025-01-20T22:02:15Z
dc.date.issued2021
dc.description.abstractCurrently, industry is undergoing an exponential increase in binary-based combinatorial problems. In this regard, metaheuristics have been a common trend in the field in order to design approaches to successfully solve them. Thus, a well-known strategy includes the employment of continuous swarm-based algorithms transformed to perform in binary environments. In this work, we propose a hybrid approach that contains discrete smartly adapted population-based strategies to efficiently tackle binary-based problems. The proposed approach employs a reinforcement learning technique, known as SARSA (State-Action-Reward-State-Action), in order to utilize knowledge based on the run time. In order to test the viability and competitiveness of our proposal, we compare discrete state-of-the-art algorithms smartly assisted by SARSA. Finally, we illustrate interesting results where the proposed hybrid outperforms other approaches, thus, providing a novel option to tackle these types of problems in industry.
dc.fuente.origenWOS
dc.identifier.doi10.3390/math9222887
dc.identifier.eissn2227-7390
dc.identifier.urihttps://doi.org/10.3390/math9222887
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/93956
dc.identifier.wosidWOS:000815316600001
dc.issue.numero22
dc.language.isoen
dc.revistaMathematics
dc.rightsacceso restringido
dc.subjectcombinatorial problems
dc.subjectmetaheuristics
dc.subjectbinarization scheme
dc.subjectSARSA
dc.subjectQ-learning
dc.subjectmachine learning
dc.subjectdiscretization methods
dc.titleA Novel Learning-Based Binarization Scheme Selector for Swarm Algorithms Solving Combinatorial Problems
dc.typeartículo
dc.volumen9
sipa.indexWOS
sipa.trazabilidadWOS;2025-01-12
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