A population based metaheuristic for the minimum latency problem

Boldizsár Tüű-Szabó, Péter Földesi, L. Kóczy

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

In this paper we present a population based metaheuristic for solving the Minimum Latency Problem, which is the combination of bacterial evolutionary algorithm with local search techniques. The algorithm was tested on TSPLIB benchmark instances, and the results are competitive in terms of accuracy and runtimes with the state-of-the art methods. Except for two instances our algorithm found the best-known solution, and for the biggest tested instance it outperformed the best-known solution. The runtime was on average 30% faster than the most efficient method in the literature.

Original languageEnglish
Title of host publicationStudies in Computational Intelligence
PublisherSpringer Verlag
Pages113-121
Number of pages9
DOIs
Publication statusPublished - Jan 1 2019

Publication series

NameStudies in Computational Intelligence
Volume796
ISSN (Print)1860-949X

Keywords

  • Delivery man problem
  • Discrete optimization
  • Metaheuristic
  • Minimum latency problem
  • Traveling repairman problem

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Tüű-Szabó, B., Földesi, P., & Kóczy, L. (2019). A population based metaheuristic for the minimum latency problem. In Studies in Computational Intelligence (pp. 113-121). (Studies in Computational Intelligence; Vol. 796). Springer Verlag. https://doi.org/10.1007/978-3-030-00485-9_13