A Binary Sine-Cosine Algorithm applied to the Knapsack problem

Hernan Pinto, Alvaro Peña, Matías Valenzuela, Andrés Fernández

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

3 Citas (Scopus)

Resumen

In industry, the concept of complex systems is becoming relevant due to the diverse applications in operations research. Many of these complex problems are NP-hard and it is difficult to approach them with complete optimization techniques. The use of metaheuristics has had good results and in particular, the design of binary algorithms based on continuous metaheuristics of swarm intelligence. In this article, we apply the binarization mechanism based on the percentile concept. We apply the percentile concept to the sine-cosine algorithm (SCOA) in order to solve the multidimensional backpack problem (MKP). The experiments are designed to demonstrate the usefulness of the percentile concept in binarization. In addition, we verify the efficiency of our algorithm through reference instances. The results indicate that the binary Percentile Sine-Cosine Optimization Algorithm (BPSCOA) obtains adequate results when evaluated with a combinatorial problem such as the MKP.

Idioma originalInglés
Título de la publicación alojadaArtificial Intelligence Methods in Intelligent Algorithms - Proceedings of 8th Computer Science On-line Conference 2019, Vol. 2
EditoresRadek Silhavy
EditorialSpringer Verlag
Páginas128-138
Número de páginas11
ISBN (versión impresa)9783030198091
DOI
EstadoPublicada - 2019
Publicado de forma externa
Evento8th Computer Science On-line Conference, CSOC 2019 - Prague, República Checa
Duración: 24 abr. 201927 abr. 2019

Serie de la publicación

NombreAdvances in Intelligent Systems and Computing
Volumen985
ISSN (versión impresa)2194-5357
ISSN (versión digital)2194-5365

Conferencia

Conferencia8th Computer Science On-line Conference, CSOC 2019
País/TerritorioRepública Checa
CiudadPrague
Período24/04/1927/04/19

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