The backbone of the travelling salesperson

  • Authors:

  • Philip Kilby;John Slaney;Toby Walsh

  • Affiliations:

  • ANU, Canberra, Australia;NICTA, Canberra, Australia and ANU, Canberra, Australia;NICTA, Sydney, Australia and UNSW, Sydney, Australia

  • Venue:
  • IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
  • Year:
  • 2005

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Abstract

We study the backbone of the travelling salesperson optimization problem. We prove that it is intractable to approximate the backbone with any performance guarantee, assuming that P≠NP and there is a limit on the number of edges falsely returned. Nevertheless, in practice, it appears that much of the backbone is present in close to optimal solutions. We can therefore often find much of the backbone using approximation methods based on good heuristics. We demonstrate that such backbone information can be used to guide the search for an optimal solution. However, the variance in runtimes when using a backbone guided heuristic is large. This suggests that we may need to combine such heuristics with randomization and restarts. In addition, though backbone guided heuristics are useful for finding optimal solutions, they are less help in proving optimality.