Approximation of a modified traveling salesman problem using bacterial memetic algorithms

Márk Farkas, Péter Földesi, János Botzheim, László T. Kóczy

Research output: Chapter in Book/Report/Conference proceedingChapter

7 Citations (Scopus)

Abstract

The goal of this paper is to develop an algorithm that is capable to handle a slightly modified version of the minimal Traveling Salesman Problem in an efficient and robust way and produces high-quality solutions within a reasonable amount of time. The requirements of practical logistical applications, such as road transportation and supply chains, are also taken into consideration in this novel approach of the TSP. This well-known combinatorial optimization task is solved by a bacterial memetic algorithm, which is an evolutionary algorithm inspired by bacterial transduction. A new method is also proposed to deal with the time dependency in the cost matrix. The efficiency of the implementation, including time and space constraints, is investigated on a real life problem.

Original languageEnglish
Title of host publicationTowards Intelligent Engineering and Information Technology
EditorsImre Rudas, Janos Fodor, Janusz Kacprzyk
Pages607-625
Number of pages19
DOIs
Publication statusPublished - Dec 1 2009

Publication series

NameStudies in Computational Intelligence
Volume243
ISSN (Print)1860-949X

Keywords

  • Eugenic bacterial memetic algorithm
  • Time dependent fuzzy costs
  • Traveling Salesman Problem

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Farkas, M., Földesi, P., Botzheim, J., & Kóczy, L. T. (2009). Approximation of a modified traveling salesman problem using bacterial memetic algorithms. In I. Rudas, J. Fodor, & J. Kacprzyk (Eds.), Towards Intelligent Engineering and Information Technology (pp. 607-625). (Studies in Computational Intelligence; Vol. 243). https://doi.org/10.1007/978-3-642-03737-5_44