A Percentile Firefly Algorithm an Application to the Set Covering Problem

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Abstract

The application of continuous metaheuristic algorithms to combinatorial problems is an area of interest at the engineering level. This interest is related to the fact that many of the problems that are addressed at the industrial level are of the combinatorial type and a not lesser subset of these are of the NP-hard type. In this article, we propose a binarization mechanism for continuous metaheuristics that uses the concept of percentile. This percentile concept is applied to the firefly optimization algorithm to solve the set covering problem (SCP). To determine the importance of the percentile concept, experiments were designed to identify its contribution. Additionally, to see that the proposal is adequate, the efficiency of the algorithm is compared using reference instances. The results indicate that the binary percentile firefly algorithm (BPFA) obtains adequate results when evaluated with a combinatorial problem such as the SCP.

Original languageEnglish
Title of host publicationArtificial Intelligence in Intelligent Systems - Proceedings of 10th Computer Science On-line Conference, 2021
EditorsRadek Silhavy
PublisherSpringer Science and Business Media Deutschland GmbH
Pages750-759
Number of pages10
ISBN (Print)9783030774448
DOIs
StatePublished - 2021
Externally publishedYes
Event10th Computer Science Online Conference, CSOC 2021 - Virtual, Online
Duration: 1 Apr 20211 Apr 2021

Publication series

NameLecture Notes in Networks and Systems
Volume229
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference10th Computer Science Online Conference, CSOC 2021
CityVirtual, Online
Period1/04/211/04/21

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