A Percentil Gravitational Search Algorithm an Aplication to the Set Covering Problem

Leonardo Pavez, Francisco Altimiras, Gabriel Villavicencio

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

1 Scopus citations

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 gravitational search algorithm (BPGSA) obtains adequate results when evaluated with a combinatorial problem such as the SCP.

Original languageEnglish
Title of host publicationSoftware Engineering Perspectives in Intelligent Systems - Proceedings of 4th Computational Methods in Systems and Software 2020
EditorsRadek Silhavy, Petr Silhavy, Zdenka Prokopova
PublisherSpringer Science and Business Media Deutschland GmbH
Pages663-673
Number of pages11
ISBN (Print)9783030633189
DOIs
StatePublished - 2020
Event4th Computational Methods in Systems and Software, CoMeSySo 2020 - Vsetin, Czech Republic
Duration: 14 Oct 202017 Oct 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1295
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference4th Computational Methods in Systems and Software, CoMeSySo 2020
Country/TerritoryCzech Republic
CityVsetin
Period14/10/2017/10/20

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