A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem

Mersmann Olaf, Bischl Bernd,Trautmann Heike, Wagner Markus, Bossek Jakob, Neumann Frank


Zusammenfassung
Meta-heuristics are frequently used to tackle NP-hard combinatorial optimization problems. With this paper we contribute to the understanding of the success of 2-opt based local search algorithms for solving the traveling salesperson problem (TSP). Although 2-opt is widely used in practice, it is hard to understand its success from a theoretical perspective. We take a statistical approach and examine the features of TSP instances that make the problem either hard or easy to solve. As a measure of problem difficulty for 2-opt we use the approximation ratio that it achieves on a given instance. Our investigations point out important features that make TSP instances hard or easy to be approximated by 2-opt. © 2013 Springer Science+Business Media Dordrecht.



Publikationstyp
Aufsatz (Zeitschrift)

Begutachtet
Ja

Publikationsstatus
Veröffentlicht

Jahr
2013

Fachzeitschrift
Annals of Mathematics and Artificial Intelligence

Band
69

Ausgabe
2

Erste Seite
182

Seiten
151-182

Sprache
Englisch

ISSN
10122443

DOI

Affiliierungen
Universitat Dortmund,University of Adelaide