A binary ant lion optimisation algorithm applied to the set covering problem

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 Ant Lion Algorithm (BALO) obtains adequate results when evaluated with a combinatorial problem such as the SCP.

Original languageEnglish
Title of host publicationArtificial Intelligence Methods in Intelligent Algorithms - Proceedings of 8th Computer Science On-line Conference 2019, Vol. 2
EditorsRadek Silhavy
PublisherSpringer Verlag
Pages156-167
Number of pages12
ISBN (Print)9783030198091
DOIs
StatePublished - 1 Jan 2019
Event8th Computer Science On-line Conference, CSOC 2019 - Prague, Czech Republic
Duration: 24 Apr 201927 Apr 2019

Publication series

NameAdvances in Intelligent Systems and Computing
Volume985
ISSN (Print)2194-5357

Conference

Conference8th Computer Science On-line Conference, CSOC 2019
CountryCzech Republic
CityPrague
Period24/04/1927/04/19

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