Discrete bacterial memetic evolutionary algorithm for the time dependent traveling salesman problem

Boldizsár Tüű-Szabó, Péter Földesi, L. Kóczy

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

4 Citations (Scopus)

Abstract

The Time Dependent Traveling Salesman Problem (TDTSP) that is addressed in this paper is a variant of the well-known Traveling Salesman Problem. In this problem the distances between nodes vary in time (are longer in rush hours in the city centre), Our Discrete Bacterial Evolutionary Algorithm (DBMEA) was tested on benchmark problems (on bier127 and on a self-generated problem with 250 nodes) with various jam factors. The results demonstrate the effectiveness of the algorithm.

Original languageEnglish
Title of host publicationInformation Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations - 17th International Conference, IPMU 2018, Proceedings
PublisherSpringer Verlag
Pages523-533
Number of pages11
ISBN (Print)9783319914725
DOIs
Publication statusPublished - Jan 1 2018
Event17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2018 - Cadiz, Spain
Duration: Jun 11 2018Jun 15 2018

Publication series

NameCommunications in Computer and Information Science
Volume853
ISSN (Print)1865-0929

Other

Other17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2018
CountrySpain
CityCadiz
Period6/11/186/15/18

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Keywords

  • Heuristic
  • Time dependent
  • Traveling salesman problem

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

Cite this

Tüű-Szabó, B., Földesi, P., & Kóczy, L. (2018). Discrete bacterial memetic evolutionary algorithm for the time dependent traveling salesman problem. In Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations - 17th International Conference, IPMU 2018, Proceedings (pp. 523-533). (Communications in Computer and Information Science; Vol. 853). Springer Verlag. https://doi.org/10.1007/978-3-319-91473-2_45