TY - GEN

T1 - A Machine Learning Whale Algorithm Applied to the Matrix Covering Problem

AU - Valenzuela, Matias

AU - Moraga, Paola

AU - Causa, Leonardo

AU - Pinto, Hernan

AU - Rubio, José Miguel

N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

PY - 2021

Y1 - 2021

N2 - In the industry, the need for optimization naturally arises, with which there is a large number of optimization problems, particularly combinatorial and NP-hard type. Therefore, there is an important motivation for the development of algorithms that address these types of problems. IN this line, a large number of metaheuristic algorithms have been developed which work only in continuous spaces. Modifying the latter in order to address combinatorial problems has important applications. In this article, we will study a general binarization mechanism of continuous metaheuristics based on clustering techniques and it will be applied to the whale algorithm. Experiments are designed in order to demonstrate the contribution of the clustering technique in the binarization process. The results indicate that the Ballena binary optimization algorithm (MLWH) obtains adequate results when it is evaluated with a combinatorial problem such as the SCP.

AB - In the industry, the need for optimization naturally arises, with which there is a large number of optimization problems, particularly combinatorial and NP-hard type. Therefore, there is an important motivation for the development of algorithms that address these types of problems. IN this line, a large number of metaheuristic algorithms have been developed which work only in continuous spaces. Modifying the latter in order to address combinatorial problems has important applications. In this article, we will study a general binarization mechanism of continuous metaheuristics based on clustering techniques and it will be applied to the whale algorithm. Experiments are designed in order to demonstrate the contribution of the clustering technique in the binarization process. The results indicate that the Ballena binary optimization algorithm (MLWH) obtains adequate results when it is evaluated with a combinatorial problem such as the SCP.

UR - http://www.scopus.com/inward/record.url?scp=85120671889&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-90321-3_33

DO - 10.1007/978-3-030-90321-3_33

M3 - Conference contribution

AN - SCOPUS:85120671889

SN - 9783030903206

T3 - Lecture Notes in Networks and Systems

SP - 413

EP - 422

BT - Data Science and Intelligent Systems - Proceedings of 5th Computational Methods in Systems and Software 2021

A2 - Silhavy, Radek

A2 - Silhavy, Petr

A2 - Prokopova, Zdenka

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 1 October 2021 through 1 October 2021

ER -