TY - GEN
T1 - A Percentil Bat Algorithm an Application to the Set Covering Problem
AU - JORQUERA MARTINEZ, LORENA VERONICA
AU - VALENZUELA TORO, PAMELA ISABEL
AU - Altimiras, Francisco
AU - Moraga, Paola
AU - Villavicencio, Gabriel
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - The study and understanding of algorithms that solve combinatorial problems based on swarm intelligence continuous metaheuristics, is an area of interest at the level of basic and applied science. This is due to the fact that many of the problems addressed at industrial level are of a combinatorial type and a subset no less than these are of the NP-hard type. In this article, a mechanism of binarization of continuous metaheuristics that uses the concept of the percentile is proposed. This percentile concept is applied to the An Lion optimization algorithm, solving the set covering problem (SCP). Experiments were designed to demonstrate the importance of the percentile concept in the binarization process. Subsequently, the efficiency of the algorithm is verified through reference instances. The results indicate that the binary percentile bat Algorithm (BPBA) obtains adequate results when evaluated with a combinatorial problem such as the SCP.
AB - The study and understanding of algorithms that solve combinatorial problems based on swarm intelligence continuous metaheuristics, is an area of interest at the level of basic and applied science. This is due to the fact that many of the problems addressed at industrial level are of a combinatorial type and a subset no less than these are of the NP-hard type. In this article, a mechanism of binarization of continuous metaheuristics that uses the concept of the percentile is proposed. This percentile concept is applied to the An Lion optimization algorithm, solving the set covering problem (SCP). Experiments were designed to demonstrate the importance of the percentile concept in the binarization process. Subsequently, the efficiency of the algorithm is verified through reference instances. The results indicate that the binary percentile bat Algorithm (BPBA) obtains adequate results when evaluated with a combinatorial problem such as the SCP.
UR - http://www.scopus.com/inward/record.url?scp=85089720211&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-51971-1_18
DO - 10.1007/978-3-030-51971-1_18
M3 - Conference contribution
AN - SCOPUS:85089720211
SN - 9783030519704
T3 - Advances in Intelligent Systems and Computing
SP - 223
EP - 233
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 -