Skip to main content

A Method to Compute the Sparse Graphs for Traveling Salesman Problem Based on Frequency Quadrilaterals

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10823))

Abstract

In this paper, an iterative algorithm is designed to compute the sparse graphs for traveling salesman problem (TSP) according to the frequency quadrilaterals so that the computation time of the algorithms for TSP will be lowered. At each computation cycle, the algorithm first computes the average frequency \( \overline{f} (e) \) of an edge e with N frequency quadrilaterals containing e in the input graph G(V, E). Then the 1/3|E| edges with low frequency are eliminated to generate the output graph with a smaller number of edges. The algorithm can be iterated several times and the original optimal Hamiltonian cycle is preserved with a high probability. The experiments demonstrate the algorithm computes the sparse graphs with the O(nlog2 n) edges containing the original optimal Hamiltonian cycle for most of the TSP instances in the TSPLIB. The computation time of the iterative algorithm is O(Nn 2).

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Karp, R.M.: On the computational complexity of combinatorial problems. Networks (U.S.A.) 5(1), 45–68 (1975)

    MATH  Google Scholar 

  2. Gutin, G., Punnen, A.P. (eds.): The Traveling Salesman Problem and Its Variations. Springer, New York (2007). https://doi.org/10.1007/b101971

    MATH  Google Scholar 

  3. Held, M., Karp, R.M.: A dynamic programming approach to sequencing problems. J. Soc. Ind. Appl. Math. 10(1), 196–210 (1962)

    Article  MathSciNet  MATH  Google Scholar 

  4. Bellman, R.: Dynamic programming treatment of the travelling salesman problem. J. ACM 9(1), 61–63 (1962)

    Article  MathSciNet  MATH  Google Scholar 

  5. de Klerk, E., Dobre, C.: A comparison of lower bounds for the symmetric circulant traveling salesman problem. Discret. Appl. Math. 159(16), 1815–1826 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  6. Levine, M.S.: Finding the right cutting planes for the TSP. ACM J. Exp. Algorithmics (JEA) 5(6), 1–20 (2000)

    MATH  Google Scholar 

  7. Applegate, D.L., Bixby, R.E., Chvátal, V., Cook, W., Espinoza, D.G., Goycoolea, M., Helsgaun, K.: Certification of an optimal TSP tour through 85900 cities. Oper. Res. Lett. 37(1), 11–15 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  8. Thomas, H.C., Charles, E.L., Ronald, L.R., Clifford, S.: Introduction to Algorithm, 2nd edn. China Machine Press, Beijing (2006)

    Google Scholar 

  9. Hoogeveen, J.A.: Analysis of Christofides’ heuristic: some paths are more difficult than cycles. Oper. Res. Lett. 10(5), 291–295 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  10. Helsgaun, K.: An effective implementation of the Lin-Kernighan traveling salesman heuristic (2012). www2.iwr.uni-heidelberg.de/groups/comopt/software/TSPLIB95/tsp/

  11. Björklund, A., Husfeldt, T., Kaski, P., Koivisto, M.: The traveling salesman problem in bounded degree graphs. ACM Transit. Algorithms 8(2), 1–18 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  12. Gharan, S.O., Saberi, A.: The asymmetric traveling salesman problem on graphs with bounded genus. In: SODA 2011 Proceedings of the Twenty-Second Annual ACMSIAM Symposium on Discrete Algorithms, pp. 967–975. ACM, New York (2011)

    Google Scholar 

  13. Bartal, Y., Gottlieb, L.A., Krauthgamer, R.: The traveling salesman problem: low-dimensionality implies a polynomial time approximation scheme. In: STOC 2012: Proceedings of the Forty-Fourth Annual ACM Symposium on Theory of Computing, pp. 663–672. ACM, New York (2012)

    Google Scholar 

  14. Hougardy, S., Schroeder, R.T.: Edge elimination in TSP instances. In: Kratsch, D., Todinca, I. (eds.) WG 2014. LNCS, vol. 8747, pp. 275–286. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-12340-0_23

    Google Scholar 

  15. Wang, Y.: A representation model for TSP. In: 15th IEEE International Conference on High Performance Computing and Communications, HPCC 2013 and 11th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing, pp. 204–209. IEEE, New York (2013)

    Google Scholar 

  16. Wang, Y.: An approximate method to compute a sparse graph for traveling salesman problem. Expert Syst. App. 42(12), 5150–5162 (2015)

    Article  Google Scholar 

  17. Wang, Y.: Statistical analysis of frequency graph for traveling salesman problem. J. Intell. Fuzzy Syst. 28(3), 1109–1118 (2015)

    MathSciNet  Google Scholar 

  18. Wang, Y., Remmel, J.B.: A binomial distribution model for the traveling salesman problem based on frequency quadrilaterals. J. Graph Algorithms App. 20(2), 411–434 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  19. Wang, Y.: An approximate algorithm for triangle TSP with a four-vertex three-line inequality. Int. J. Appl. Metaheuristic Comput. 6(1), 35–46 (2015)

    Article  Google Scholar 

  20. Reinelt, G. (2016). http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/

  21. Mittelmann, H.: NEOS Server for Concorde (2016). http://neos-server.org/neos/solvers/co:concorde/TSP.html

Download references

Acknowledgement

The authors acknowledge the anonymous referees for their suggestions to improve the paper. We acknowledge W. Cook, H. Mittelmann who created the Concorde and G. Reinelt, et al. who provided the TSP data to TSPLIB. The authors acknowledge the funds supported by NSFC (No. 51205129) and the Fundamental Research Funds for the Central Universities (No. 2015ZD10). We also thank the support of Beijing Key Laboratory of Energy Safety and Clean Utilization.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yong Wang .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Wang, Y., Remmel, J. (2018). A Method to Compute the Sparse Graphs for Traveling Salesman Problem Based on Frequency Quadrilaterals. In: Chen, J., Lu, P. (eds) Frontiers in Algorithmics. FAW 2018. Lecture Notes in Computer Science(), vol 10823. Springer, Cham. https://doi.org/10.1007/978-3-319-78455-7_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-78455-7_22

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-78454-0

  • Online ISBN: 978-3-319-78455-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics