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, Paola
AU - Pinto, Hernan
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
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 -