A percentile multi-verse optimizer algorithm applied to the knapsack problem

Matias Valenzuela, Pamela Valenzuela, Camilo Caceres, Lorena Jorquera, Hernan Pinto

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

Resumen

Many problems addressed in operational research are combinatorial and NP-hard type. Therefore, designing binary algorithms based on swarm intelligence continuous metaheuristics is an area of interest in operational research. In this paper we use a general binarization mechanism based on the percentile concept. We apply the percentile concept to multiverse optimizer algorithm to solve multidimensional knapsack problem (MKP). Experiments are designed to demonstrate the utility of the percentile concept in binarization. Additionally, we verify the efficiency of our algorithm through benchmark instances, showing that Binary multi-verse Optimizer (BMVO) obtains adequate results when it is evaluated against another state of the art algorithm.

Idioma originalInglés
Título de la publicación alojadaProceedings of CISTI 2019 - 14th Iberian Conference on Information Systems and Technologies
EditoresAlvaro Rocha, Isabel Pedrosa, Manuel Perez Cota, Ramiro Goncalves
EditorialIEEE Computer Society
ISBN (versión digital)9789899843493
DOI
EstadoPublicada - jun 2019
Publicado de forma externa
Evento14th Iberian Conference on Information Systems and Technologies, CISTI 2019 - Coimbra, Portugal
Duración: 19 jun 201922 jun 2019

Serie de la publicación

NombreIberian Conference on Information Systems and Technologies, CISTI
Volumen2019-June
ISSN (versión impresa)2166-0727
ISSN (versión digital)2166-0735

Conferencia

Conferencia14th Iberian Conference on Information Systems and Technologies, CISTI 2019
País/TerritorioPortugal
CiudadCoimbra
Período19/06/1922/06/19

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