Solving the 0/1 Knapsack Problem Using a Galactic Swarm Optimization with Data-Driven Binarization Approaches

Camilo Vásquez, José Lemus-Romani, BRODERICK CRAWFORD LABRIN, RICARDO JAVIER SOTO DE GIORGIS, Gino Astorga, WENCESLAO ENRIQUE PALMA MUÑOZ, Sanjay Misra, Fernando Paredes

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

Abstract

Metaheuristics are used to solve high complexity problems, where resolution by exact methods is not a viable option since the resolution time when using these exact methods is not acceptable. Most metaheuristics are defined to solve problems of continuous optimization, which forces these algorithms to adapt its work in the discrete domain using discretization techniques to solve complex problems. This paper proposes data-driven binarization approaches based on clustering techniques. We solve different instances of Knapsack Problems with Galactic Swarm Optimization algorithm using this machine learning techniques.

Original languageEnglish
Title of host publicationComputational Science and Its Applications – ICCSA 2020 - 20th International Conference, Proceedings
EditorsOsvaldo Gervasi, Beniamino Murgante, Sanjay Misra, Chiara Garau, Ivan Blecic, David Taniar, Bernady O. Apduhan, Ana Maria A.C. Rocha, Eufemia Tarantino, Carmelo Maria Torre, Yeliz Karaca
PublisherSpringer Science and Business Media Deutschland GmbH
Pages511-526
Number of pages16
ISBN (Print)9783030588168
DOIs
StatePublished - 2020
Externally publishedYes
Event20th International Conference on Computational Science and Its Applications, ICCSA 2020 - Cagliari, Italy
Duration: 1 Jul 20204 Jul 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12254 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Computational Science and Its Applications, ICCSA 2020
CountryItaly
CityCagliari
Period1/07/204/07/20

Keywords

  • DBSCAN
  • Galactic Swarm Optimization
  • K-means
  • Knapsack problem
  • Machine learning
  • Metaheuristic

Fingerprint Dive into the research topics of 'Solving the 0/1 Knapsack Problem Using a Galactic Swarm Optimization with Data-Driven Binarization Approaches'. Together they form a unique fingerprint.

Cite this