A binary machine learning cuckoo search algorithm improved by a local search operator for the set-union knapsack problem

José García, José Lemus-Romani, Francisco Altimiras, Broderick Crawford, Ricardo Soto, Marcelo Becerra-Rozas, Paola Moraga, Alex Paz Becerra, Alvaro Peña Fritz, Jose Miguel Rubio, Gino Astorga

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

3 Citas (Scopus)

Resumen

Optimization techniques, specially metaheuristics, are constantly refined in order to de-crease execution times, increase the quality of solutions, and address larger target cases. Hybridizing techniques are one of these strategies that are particularly noteworthy due to the breadth of applica-tions. In this article, a hybrid algorithm is proposed that integrates the k-means algorithm to generate a binary version of the cuckoo search technique, and this is strengthened by a local search operator. The binary cuckoo search algorithm is applied to the N P-hard Set-Union Knapsack Problem. This problem has recently attracted great attention from the operational research community due to the breadth of its applications and the difficulty it presents in solving medium and large instances. Numerical experiments were conducted to gain insight into the contribution of the final results of the k-means technique and the local search operator. Furthermore, a comparison to state-of-the-art algorithms is made. The results demonstrate that the hybrid algorithm consistently produces superior results in the majority of the analyzed medium instances, and its performance is competitive, but degrades in large instances.

Idioma originalInglés
Número de artículo2611
PublicaciónMathematics
Volumen9
N.º20
DOI
EstadoPublicada - 2 oct. 2021
Publicado de forma externa

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