A Percentil Bat Algorithm an Application to the Set Covering Problem

LORENA VERONICA JORQUERA MARTINEZ, PAMELA ISABEL VALENZUELA TORO, Francisco Altimiras, Paola Moraga, Gabriel Villavicencio

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

Abstract

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.

Original languageEnglish
Title of host publicationArtificial Intelligence and Bioinspired Computational Methods - Proceedings of the 9th Computer Science On-line Conference, CSOC 2020
EditorsRadek Silhavy
PublisherSpringer
Pages223-233
Number of pages11
ISBN (Print)9783030519704
DOIs
StatePublished - 2020
Externally publishedYes
Event9th Computer Science On-line Conference, CSOC 2020 - Zlin, Czech Republic
Duration: 15 Jul 202015 Jul 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1225 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference9th Computer Science On-line Conference, CSOC 2020
CountryCzech Republic
CityZlin
Period15/07/2015/07/20

Fingerprint Dive into the research topics of 'A Percentil Bat Algorithm an Application to the Set Covering Problem'. Together they form a unique fingerprint.

Cite this