A binary ant lion optimizer applied to knapsack problem

Matias Valenzuela, LORENA VERONICA JORQUERA MARTINEZ, Gabriel Villavicencio, Paola Moraga, Hernan Pinto

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

Abstract

Combinatorial problems with NP-hard complexity appear frequently in operational research. Making robust algorithms that solve these combinatorial problems is of interest in operational research. In this article, a binarization mechanism is proposed so that continuous metaheuristics can solve combinatorial problems. The binarization mechanism uses the concept of percentile. This percentile mechanism is applied to the ant lion algorithm. The NP-hard knapsack problem (MKP) was used to verify our algorithm. Additionally, the binary percentile algorithm was compared with other algorithms that have recently has solved the MKP, observing that the percentile algorithm produces competitive results.

Original languageEnglish
Title of host publication2019 6th International Conference on Systems and Informatics, ICSAI 2019
EditorsWanqing Wu, Lipo Wang, Chunlei Ji, Niansheng Chen, Sun Qiang, Xiaoyong Song, Xin Wang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages469-474
Number of pages6
ISBN (Electronic)9781728152561
DOIs
StatePublished - Nov 2019
Externally publishedYes
Event6th International Conference on Systems and Informatics, ICSAI 2019 - Shanghai, China
Duration: 2 Nov 20194 Nov 2019

Publication series

Name2019 6th International Conference on Systems and Informatics, ICSAI 2019

Conference

Conference6th International Conference on Systems and Informatics, ICSAI 2019
CountryChina
CityShanghai
Period2/11/194/11/19

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