A K-Means Grasshopper Optimisation Algorithm Applied to the Set Covering Problem

Gabriel Villavicencio, Matias Valenzuela, Francisco Altimiras, Paola Moraga, Hernan Pinto

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


Many of the problems addressed at the industrial level are of a combinatorial type and a sub-assembly not less than these are of the NP-hard type. The design of algorithms that solve combinatorial problems based on the continuous metaheuristic of swarm intelligence is an area of interest at an industrial level. In this article, we explore a general binarization mechanism of continuous metaheuristics based on the k-means technique. In particular, we apply the k-means technique to the Grasshopper optimization algorithm in order to solve the set covering problem (SCP). The experiments are designed with the aim of demonstrating the usefulness of the k-means technique in binarization. Additionally, we verify the effectiveness of our algorithm through reference instances. The results indicate the K-means binary grasshopper optimization algorithm (KBGOA) obtains adequate results when evaluated with a combinatorial problem such as the SCP.

Original languageEnglish
Title of host publicationArtificial Intelligence and Bioinspired Computational Methods - Proceedings of the 9th Computer Science On-line Conference, CSOC 2020
EditorsRadek Silhavy
Number of pages12
ISBN (Print)9783030519704
StatePublished - 2020
Externally publishedYes
Event9th Computer Science On-line Conference, CSOC 2020 - Zlin, Czech Republic
Duration: 15 Jul 202015 Jul 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1225 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365


Conference9th Computer Science On-line Conference, CSOC 2020
Country/TerritoryCzech Republic


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