A Percentil Bat Algorithm an Application to the Set Covering Problem

Lorena Jorquera, Pamela Valenzuela, Francisco Altimiras, Paola Moraga, Gabriel Villavicencio

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

The study and understanding of algorithms that solve combinatorial problems based on swarm intelligence continuous metaheuristics, is an area of interest at the level of basic and applied science. This is due to the fact that many of the problems addressed at industrial level are of a combinatorial type and a subset no less than these are of the NP-hard type. In this article, a mechanism of binarization of continuous metaheuristics that uses the concept of the percentile is proposed. This percentile concept is applied to the An Lion optimization algorithm, solving the set covering problem (SCP). Experiments were designed to demonstrate the importance of the percentile concept in the binarization process. Subsequently, the efficiency of the algorithm is verified through reference instances. The results indicate that the binary percentile bat Algorithm (BPBA) obtains adequate results when evaluated with a combinatorial problem such as the SCP.

Idioma originalInglés
Título de la publicación alojadaArtificial Intelligence and Bioinspired Computational Methods - Proceedings of the 9th Computer Science On-line Conference, CSOC 2020
EditoresRadek Silhavy
EditorialSpringer
Páginas223-233
Número de páginas11
ISBN (versión impresa)9783030519704
DOI
EstadoPublicada - 2020
Evento9th Computer Science On-line Conference, CSOC 2020 - Zlin, República Checa
Duración: 15 jul. 202015 jul. 2020

Serie de la publicación

NombreAdvances in Intelligent Systems and Computing
Volumen1225 AISC
ISSN (versión impresa)2194-5357
ISSN (versión digital)2194-5365

Conferencia

Conferencia9th Computer Science On-line Conference, CSOC 2020
País/TerritorioRepública Checa
CiudadZlin
Período15/07/2015/07/20

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