A Comparison of Nature Inspired Heuristics on the Traveling Salesman Problem

  • Thomas Stützle
  • Andreas Grün
  • Sebastian Linke
  • Marco Rüttger
Conference paper

DOI: 10.1007/3-540-45356-3_65

Part of the Lecture Notes in Computer Science book series (LNCS, volume 1917)
Cite this paper as:
Stützle T., Grün A., Linke S., Rüttger M. (2000) A Comparison of Nature Inspired Heuristics on the Traveling Salesman Problem. In: Schoenauer M. et al. (eds) Parallel Problem Solving from Nature PPSN VI. PPSN 2000. Lecture Notes in Computer Science, vol 1917. Springer, Berlin, Heidelberg

Abstract

The Traveling Salesman Problem is a standard test-bed for algorithmic ideas. Currently, there exists a large number of nature-inspired algorithms for (he TSP and for some of these approaches very good performance is reported. In particular, the best performing approaches combine solution modification or construction with the subsequent application of a fast and effective local search algorithm. Yet, comparisons between these algorithms with respect to performance are often difficult due to different implementation choices of which the one of the local search algorithm is particularly critical. In this article we experimentally compare some of the best performing recently proposed nature-inspired algorithms which improve solutions by using a same local search algorithm and investigate their performance on a large set of benchmark instances.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Thomas Stützle
    • 1
    • 2
  • Andreas Grün
    • 1
  • Sebastian Linke
    • 1
  • Marco Rüttger
    • 1
  1. 1.Computer Science DepartmentDarmstadt University of TechnologyDarmstadt
  2. 2.IRIDIAUniversité Libre de BruxellesBrusselsBelgium

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