TY - GEN

T1 - A K-Means Grasshopper Optimisation Algorithm Applied to the Set Covering Problem

AU - Villavicencio, Gabriel

AU - Valenzuela, Matias

AU - Altimiras, Francisco

AU - MORAGA CONTRERAS, PAOLA ALEJANDRA

AU - PINTO ARANCET, HERNAN ANDRES

N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020

Y1 - 2020

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85089716968&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-51971-1_25

DO - 10.1007/978-3-030-51971-1_25

M3 - Conference contribution

AN - SCOPUS:85089716968

SN - 9783030519704

T3 - Advances in Intelligent Systems and Computing

SP - 312

EP - 323

BT - Artificial Intelligence and Bioinspired Computational Methods - Proceedings of the 9th Computer Science On-line Conference, CSOC 2020

A2 - Silhavy, Radek

PB - Springer

Y2 - 15 July 2020 through 15 July 2020

ER -