A binary percentile sin-cosine optimisation algorithm applied to the set covering problem

Andrés Fernández, ALVARO RODRIGO PEÑA FRITZ, Matías Valenzuela, HERNAN ANDRES PINTO ARANCET

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

1 Scopus citations

Abstract

Today there is a line of research-oriented to the design of algorithms inspired by nature. Many of these algorithms work in continuous spaces. On the other hand, there is a great amount of combinatorial optimization problems (COP) which have application in the industry. The adaptation of these continuous algorithms to resolve COP is of great interest in the area of computer science. In this article we apply the percentile concept to perform the binary adaptation of the Sine-Cosine algorithm. To evaluate the results of this adaptation we will use the set covering problem (SCP). The experiments are designed with the objective of demonstrating the usefulness of the percentile concept in binarization. In addition, we verify the effectiveness of our algorithm through reference instances. The results indicate that the binary Percentile Sine-Cosine Optimization Algorithm (BPSCOA) obtains adequate results when evaluated with a combinatorial problem such as the SCP.

Original languageEnglish
Title of host publicationComputational and Statistical Methods in Intelligent Systems
EditorsRadek Silhavy, Petr Silhavy, Zdenka Prokopova
PublisherSpringer Verlag
Pages285-295
Number of pages11
ISBN (Print)9783030002107
DOIs
StatePublished - 2019
Externally publishedYes
Event2nd Computational Methods in Systems and Software, CoMeSySo 2018 - Szczecin, Poland
Duration: 12 Sep 201814 Sep 2018

Publication series

NameAdvances in Intelligent Systems and Computing
Volume859
ISSN (Print)2194-5357

Conference

Conference2nd Computational Methods in Systems and Software, CoMeSySo 2018
CountryPoland
CitySzczecin
Period12/09/1814/09/18

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