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

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

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.

Idioma originalInglés
Título de la publicación alojadaComputational and Statistical Methods in Intelligent Systems
EditoresRadek Silhavy, Petr Silhavy, Zdenka Prokopova
EditorialSpringer Verlag
Páginas285-295
Número de páginas11
ISBN (versión impresa)9783030002107
DOI
EstadoPublicada - 2019
Publicado de forma externa
Evento2nd Computational Methods in Systems and Software, CoMeSySo 2018 - Szczecin, Polonia
Duración: 12 sep 201814 sep 2018

Serie de la publicación

NombreAdvances in Intelligent Systems and Computing
Volumen859
ISSN (versión impresa)2194-5357

Conferencia

Conferencia2nd Computational Methods in Systems and Software, CoMeSySo 2018
PaísPolonia
CiudadSzczecin
Período12/09/1814/09/18

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