A memetic version of the bacterial evolutionary algorithm for discrete optimization problems

Boldizsár Tüű-Szabó, Péter Földesi, L. Kóczy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper we present our test results with our memetic algorithm, the Discrete Bacterial Memetic Evolutionary Algorithm (DBMEA). The algorithm combines the Bacterial Evolutionary Algorithm with discrete local search techniques (2-opt and 3-opt). The algorithm has been tested on four discrete NP-hard optimization problems so far, on the Traveling Salesman Problem, and on its three variants (the Traveling Salesman Problem with Time Windows, the Traveling Repairman Problem, and the Time Dependent Traveling Salesman Problem). The DBMEA proved to be efficient for all problems: it found optimal or close-optimal solutions. For the Traveling Repairman Problem the DBMEA outperformed even the state-of-the-art methods. The preliminary version of this paper was presented at the 3rd Conference on Information Technology, Systems Research and Computational Physics, 2–5 July 2018, Cracow, Poland [1].

Original languageEnglish
Title of host publicationInformation Technology, Systems Research, and Computational Physics
EditorsLászló T. Kóczy, Radko Mesiar, László T. Kóczy, Piotr Kulczycki, Piotr Kulczycki, Janusz Kacprzyk, Rafal Wisniewski
PublisherSpringer Verlag
Pages44-55
Number of pages12
ISBN (Print)9783030180577
DOIs
Publication statusPublished - Jan 1 2020
Event3rd Conference on Information Technology, Systems Research and Computational Physics, ITSRCP 2018 - Krakow, Poland
Duration: Jul 2 2018Jul 5 2018

Publication series

NameAdvances in Intelligent Systems and Computing
Volume945
ISSN (Print)2194-5357

Conference

Conference3rd Conference on Information Technology, Systems Research and Computational Physics, ITSRCP 2018
CountryPoland
CityKrakow
Period7/2/187/5/18

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Keywords

  • Time dependent
  • Time windows
  • Traveling Repairman Problem
  • Traveling Salesman Problem

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Tüű-Szabó, B., Földesi, P., & Kóczy, L. (2020). A memetic version of the bacterial evolutionary algorithm for discrete optimization problems. In L. T. Kóczy, R. Mesiar, L. T. Kóczy, P. Kulczycki, P. Kulczycki, J. Kacprzyk, & R. Wisniewski (Eds.), Information Technology, Systems Research, and Computational Physics (pp. 44-55). (Advances in Intelligent Systems and Computing; Vol. 945). Springer Verlag. https://doi.org/10.1007/978-3-030-18058-4_4