A K-means Bat Algorithm Applied to the Knapsack Problem

Leonardo Pavez, Francisco Altimiras, Gabriel Villavicencio

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

3 Scopus citations


Combinatorial problems are frequent in the industry and in the engineering field. Many of these problems are NP-hard and can hardly be addressed with complete techniques. Therefore, the design of binary algorithms based on continuous metaheuristic swarm intelligence is an area of interest in operational research. In this article we use a general binarization mechanism based on the k-means technique. This technique is applied to the bat algorithm with the objective of solving the problem of the multidimensional backpack (MKP). The experiments are designed to demonstrate the utility of the k-means technique in binarization. In addition, we verified the efficiency of our algorithm through reference instances, showing that the k-means binary bat (BKBA) algorithm obtains adequate results when evaluated against another next-generation algorithm.

Original languageEnglish
Title of host publicationSoftware Engineering Perspectives in Intelligent Systems - Proceedings of 4th Computational Methods in Systems and Software 2020
EditorsRadek Silhavy, Petr Silhavy, Zdenka Prokopova
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages10
ISBN (Print)9783030633189
StatePublished - 2020
Event4th Computational Methods in Systems and Software, CoMeSySo 2020 - Vsetin, Czech Republic
Duration: 14 Oct 202017 Oct 2020

Publication series

NameAdvances in Intelligent Systems and Computing
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365


Conference4th Computational Methods in Systems and Software, CoMeSySo 2020
Country/TerritoryCzech Republic


  • Combinatorial optimization
  • KnapSack
  • Metaheuristics
  • k-means


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