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

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

Idioma originalInglés
Título de la publicación alojadaArtificial Intelligence Methods in Intelligent Algorithms - Proceedings of 8th Computer Science On-line Conference 2019, Vol. 2
EditoresRadek Silhavy
EditorialSpringer Verlag
Páginas156-167
Número de páginas12
ISBN (versión impresa)9783030198091
DOI
EstadoPublicada - 2019
Publicado de forma externa
Evento8th Computer Science On-line Conference, CSOC 2019 - Prague, República Checa
Duración: 24 abr 201927 abr 2019

Serie de la publicación

NombreAdvances in Intelligent Systems and Computing
Volumen985
ISSN (versión impresa)2194-5357
ISSN (versión digital)2194-5365

Conferencia

Conferencia8th Computer Science On-line Conference, CSOC 2019
País/TerritorioRepública Checa
CiudadPrague
Período24/04/1927/04/19

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