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International Conference on Information and Software Technologies

ICIST 2012: Information and Software Technologies pp 62–73Cite as

Generating High Quality Candidate Sets by Tour Merging for the Traveling Salesman Problem

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 319))

Abstract

One of the most important improvements for the Traveling Salesman Problem (TSP) heuristics is usage of limited size candidate sets, also known as candidate lists (CLs). CLs help to effectively reduce the search space and appropriately sorted biases the search in a more gainful direction. Besides the best known nearest-neighbor, quadrant, Delaunay or leading Helsgaun’s alpha CLs, other effective CLs can be constructed. We revise tour merging technique proposed by Applegate et al. and using multi-random-start procedure with incorporated fast 3-opt and simplified Lin-Kernighan-Helsgaun (LKH) algorithm modifications, generate tour union CLs and analyze them by comparing with the most common alternatives. In addition, we propose a criteria indicating when merging procedure should be terminated to form high quality CLs. Finally, we show a high potential of such CLs by performing the experiments with our modified LKH variant.

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References

  1. Applegate, D.L., Bixby, R.E., Chvatal, V., Cook, W.J.: The Traveling Salesman Problem: A Computational Study. Princeton University Press, Princeton (2007)

    Google Scholar 

  2. Applegate, D., Cook, W., Rohe, A.: Chained Lin-Kernighan for large traveling salesman problems. INFORMS J. Comp. 15, 82–92 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  3. Bentley, J.L.: Fast algorithms for geometric traveling salesman problems. ORSA Journal on Computing 4(4), 387–411 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  4. Boese, K.D., Kahng, A.B., Muddu, S.: A new adaptive multi-start technique for combinatorial global optimizations. Operations Research Letters 16, 101–113 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  5. Dong, C., Jäger, G., Richter, D., Molitor, P.: Effective Tour Searching for TSP by Contraction of Pseudo Backbone Edges. In: Goldberg, A.V., Zhou, Y. (eds.) AAIM 2009. LNCS, vol. 5564, pp. 175–187. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  6. Gutin, G., Punnen, A.P.: The Traveling Salesman Problem and its Variations. Kluwer Academic Publishers, Dordrecht (2002)

    MATH  Google Scholar 

  7. Helsgaun, K.: An Effective Implementation of the Lin–Kernighan Traveling Salesman Heuristic. European Journal of Operational Research 126, 106–130 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  8. Helsgaun, K.: General k-opt submoves for the Lin-Kernighan TSP heuristic. Mathematical Programming Computation, 119–163 (2009)

    Google Scholar 

  9. Johnson, D.S., McGeoch, L.A.: The traveling salesman problem: a case study. In: Aarts, E.H.L., Lenstra, J.K. (eds.) Local Search in Combinatorial Optimization, pp. 215–310. Wiley, Chichester (1997)

    Google Scholar 

  10. Li, W.: Seeking global edges for traveling salesman problem in multi-start search. Journal of Global Optimization 51(3), 515–540 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  11. Lin, S., Kernighan, B.W.: An Effective Heuristic Algorithm for the Traveling-Salesman Problem. Operations Research 21, 498–516 (1973)

    Article  MathSciNet  MATH  Google Scholar 

  12. Mobius, A., Freisleben, B., Merz, P., Schreiber, M.: Combinatorial Optimization by Iterative Partial Transcription. Physical Review E 59(4), 4667–4674 (1999)

    Article  Google Scholar 

  13. Marinakis, Y., Marinaki, M., Dounias, G.: Honey bees mating optimization algorithm for the Euclidean traveling salesman problem. Information Sciences 181(20), 4684–4698 (2011)

    Article  MathSciNet  Google Scholar 

  14. Padberg, M., Rinaldi, G.: A branch-and-cut algorithm for the resolution of large-scale symmetric traveling salesman problems. SIAM Rev. 33, 60–100 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  15. Pitsoulis, L.S., Resende, M.G.C.: Greedy Randomized Adaptive Search Procedures. In: Pardalos, P.M., Resende, M.G.C. (eds.) Handbook of Applied Optimization, pp. 178–183. Oxford University Press (2002)

    Google Scholar 

  16. Reinelt, G.: TSPLIB — A Traveling Salesman Problem Library. ORSA Journal on Computing 3(4), 376–385 (1991)

    Article  MATH  Google Scholar 

  17. Richter, D., Goldengorin, B., Jäger, G., Molitor, P.: Improving the Efficiency of Helsgaun’s Lin-Kernighan Heuristic for the Symmetric TSP. In: Janssen, J., Prałat, P. (eds.) CAAN 2007. LNCS, vol. 4852, pp. 99–111. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  18. Zhang, W., Looks, M.: A Novel Local Search Algorithm for the Traveling Salesman Problem that Exploits Backbones. In: IJCAI 2005, pp. 343–350 (2005)

    Google Scholar 

  19. TSPLIB Homepage, http://elib.zib.de/pub/mp-testdata/tsp/tsplib/tsplib.html

  20. VLSI Homepage, www.tsp.gatech.edu/vlsi/summary.html

  21. Helsgaun’s Lin-Kernighan implementation (LKH) source code, http://www.akira.ruc.dk/~keld/research/LKH/

  22. Concorde source code, http://www.tsp.gatech.edu/concorde/index.html

  23. Cygwin homepage, http://www.cygwin.com

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Author information

Authors and Affiliations

  1. Department of Multimedia Engineering, Kaunas University of Technology, Studentu St. 50-401, 416a, LT-51368, Kaunas, Lithuania

    Andrius Blazinskas & Alfonsas Misevicius

Authors
  1. Andrius Blazinskas
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  2. Alfonsas Misevicius
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Editor information

Editors and Affiliations

  1. Kaunas University of Technology, Studentu g. 50-313a, LT-51368, Kaunas, Lithuania

    Tomas Skersys  & Rimantas Butleris  & 

  2. Kaunas University of Technology, Studentu g. 50-309a, LT-51368, Kaunas, Lithuania

    Rita Butkiene

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Blazinskas, A., Misevicius, A. (2012). Generating High Quality Candidate Sets by Tour Merging for the Traveling Salesman Problem. In: Skersys, T., Butleris, R., Butkiene, R. (eds) Information and Software Technologies. ICIST 2012. Communications in Computer and Information Science, vol 319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33308-8_6

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  • DOI: https://doi.org/10.1007/978-3-642-33308-8_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33307-1

  • Online ISBN: 978-3-642-33308-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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