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

Matias Valenzuela, PAMELA ISABEL VALENZUELA TORO, Camilo Caceres, LORENA VERONICA JORQUERA MARTINEZ, Hernan Pinto

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of CISTI 2019 - 14th Iberian Conference on Information Systems and Technologies
EditorsRamiro Goncalves, Isabel Pedrosa, Manuel Perez Cota, Alvaro Rocha
PublisherIEEE Computer Society
ISBN (Electronic)9789899843493
DOIs
StatePublished - 1 Jun 2019
Event14th Iberian Conference on Information Systems and Technologies, CISTI 2019 - Coimbra, Portugal
Duration: 19 Jun 201922 Jun 2019

Publication series

NameIberian Conference on Information Systems and Technologies, CISTI
Volume2019-June
ISSN (Print)2166-0727
ISSN (Electronic)2166-0735

Conference

Conference14th Iberian Conference on Information Systems and Technologies, CISTI 2019
CountryPortugal
CityCoimbra
Period19/06/1922/06/19

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