A Percentile Methodology Applied to Binarization of Swarm Intelligence Metaheuristics

Matias Valenzuela; Hernan Pinto; Paola Moraga; Francisco Altimiras; Gabriel Villavicencio

doi:10.29333/jisem/6348

A Percentile Methodology Applied to Binarization of Swarm Intelligence Metaheuristics

Matias Valenzuela, Hernan Pinto, Paola Moraga, Francisco Altimiras, Gabriel Villavicencio

SCHOOL OF CONSTRUCTION ENGINEERING

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1 Scopus citations

Abstract

The binarization mechanisms of continuous metaheuristics are of interest in operational research. This is mainly due to the fact that there are a lot of combinatorial problems that are NP-hard. In this article, we exploit the concept of percentile as a mechanism of binarization of swarm intelligence continuous metaheuristics. To evaluate the behavior of our binary operator, the Multi-verse metaheuristic is used and applied to solve the combinatorial problem of the knapsack. The binary algorithm obtained, the binary multi-verse Optimizer (BMVO) shows good performance in solving the most difficult problems of the knapsack.

Original language	English
Article number	em0104
Journal	Journal of Information Systems Engineering and Management
Volume	4
Issue number	4
DOIs	https://doi.org/10.29333/jisem/6348
State	Published - 2019

Keywords

binarization
metaheuristics
multidimensional knapsack problem
percentile

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10.29333/jisem/6348

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abstract = "The binarization mechanisms of continuous metaheuristics are of interest in operational research. This is mainly due to the fact that there are a lot of combinatorial problems that are NP-hard. In this article, we exploit the concept of percentile as a mechanism of binarization of swarm intelligence continuous metaheuristics. To evaluate the behavior of our binary operator, the Multi-verse metaheuristic is used and applied to solve the combinatorial problem of the knapsack. The binary algorithm obtained, the binary multi-verse Optimizer (BMVO) shows good performance in solving the most difficult problems of the knapsack.",

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AU - Pinto, Hernan

AU - Moraga, Paola

AU - Altimiras, Francisco

AU - Villavicencio, Gabriel

PY - 2019

Y1 - 2019

N2 - The binarization mechanisms of continuous metaheuristics are of interest in operational research. This is mainly due to the fact that there are a lot of combinatorial problems that are NP-hard. In this article, we exploit the concept of percentile as a mechanism of binarization of swarm intelligence continuous metaheuristics. To evaluate the behavior of our binary operator, the Multi-verse metaheuristic is used and applied to solve the combinatorial problem of the knapsack. The binary algorithm obtained, the binary multi-verse Optimizer (BMVO) shows good performance in solving the most difficult problems of the knapsack.

AB - The binarization mechanisms of continuous metaheuristics are of interest in operational research. This is mainly due to the fact that there are a lot of combinatorial problems that are NP-hard. In this article, we exploit the concept of percentile as a mechanism of binarization of swarm intelligence continuous metaheuristics. To evaluate the behavior of our binary operator, the Multi-verse metaheuristic is used and applied to solve the combinatorial problem of the knapsack. The binary algorithm obtained, the binary multi-verse Optimizer (BMVO) shows good performance in solving the most difficult problems of the knapsack.

KW - binarization

KW - metaheuristics

KW - multidimensional knapsack problem

KW - percentile

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ER -

A Percentile Methodology Applied to Binarization of Swarm Intelligence Metaheuristics

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Keywords

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