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Deconstructing the Big Valley Search Space Hypothesis

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Book cover Evolutionary Computation in Combinatorial Optimization (EvoCOP 2016)

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Abstract

The big valley hypothesis suggests that, in combinatorial optimisation, local optima of good quality are clustered and surround the global optimum. We show here that the idea of a single valley does not always hold. Instead the big valley seems to de-construct into several valleys, also called ‘funnels’ in theoretical chemistry. We use the local optima networks model and propose an effective procedure for extracting the network data. We conduct a detailed study on four selected TSP instances of moderate size and observe that the big valley decomposes into a number of sub-valleys of different sizes and fitness distributions. Sometimes the global optimum is located in the largest valley, which suggests an easy to search landscape, but this is not generally the case. The global optimum might be located in a small valley, which offers a clear and visual explanation of the increased search difficulty in these cases. Our study opens up new possibilities for analysing and visualising combinatorial landscapes as complex networks.

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References

  1. Applegate, D., Bixby, R., Chvátal, V., Cook, W.: Concorde TSP solver (2003). http://www.math.uwaterloo.ca/tsp/concorde.html

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

    Article  MathSciNet  MATH  Google Scholar 

  3. Boese, K.D., Kahng, A.B., Muddu, S.: A new adaptive multi-start technique for combinatorial global optimizations. Oper. Res. Lett. 16, 101–113 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  4. Csardi, G., Nepusz, T.: The igraph software package for complex network research. Int. J. Complex Syst. 1695, 1–9 (2006)

    Google Scholar 

  5. Fruchterman, T.M.J., Reingold, E.M.: Graph drawing by force-directed placement. Softw. Pract. Exper. 21(11), 1129–1164 (1991)

    Article  Google Scholar 

  6. Hains, D.R., Whitley, L.D., Howe, A.E.: Revisiting the big valley search space structure in the TSP. J. Oper. Res. Soc. 62(2), 305–312 (2011)

    Article  Google Scholar 

  7. Kauffman, S., Levin, S.: Towards a general theory of adaptive walks on rugged landscapes. J. Theor. Biol. 128, 11–45 (1987)

    Article  MathSciNet  Google Scholar 

  8. Kauffman, S.A.: The Origins of Order. Oxford University Press, New York (1993)

    Google Scholar 

  9. Klemm, K., Flamm, C., Stadler, P.F.: Funnels in energy landscapes. Eur. Phys. J. B 63(3), 387–391 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  10. Lin, S., Kernighan, B.W.: An effective heuristic algorithm for the traveling-salesman problem. Oper. Res. 21, 498–516 (1973)

    Article  MathSciNet  MATH  Google Scholar 

  11. Lourenço, H.R., Martin, O.C., Stützle, T.: Iterated local search. In: Handbook of Metaheuristics, pp. 320–353 (2003)

    Google Scholar 

  12. Martin, O., Otto, S.W., Felten, E.W.: Large-step Markov chains for the TSP incorporating local search heuristics. Oper. Res. Lett. 11, 219–224 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  13. Merz, P., Freisleben, B.: Memetic algorithms and the fitness landscape of the graph bi-partitioning problem. In: Eiben, A.E., Bäck, T., Schoenauer, M., Schwefel, H.-P. (eds.) PPSN 1998. LNCS, vol. 1498, p. 765. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  14. Miller, M.A., Wales, D.J.: The double-funnel energy landscape of the 38-atom Lennard-Jones cluster. J. Chem. Phys. 110(14), 6896–6906 (1999)

    Article  Google Scholar 

  15. Nešetřil, J., Milková, E., Nešetřilová, H.: Otakar Borůvka on minimum spanning tree problem translation of both the 1926 papers, comments, history. Discrete Math. 233(1–3), 3–36 (2001)

    MathSciNet  MATH  Google Scholar 

  16. Newman, M.E.J.: Networks: An Introduction. Oxford University Press, Oxford (2010)

    Book  MATH  Google Scholar 

  17. Ochoa, G., Chicano, F., Tinos, R., Whitley, D.: Tunnelling crossover networks. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pp. 449–456. ACM (2015)

    Google Scholar 

  18. Ochoa, G., Tomassini, M., Verel, S., Darabos, C.: A study of NK landscapes’ basins and local optima networks. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO). pp. 555–562. ACM (2008)

    Google Scholar 

  19. Ochoa, G., Veerapen, N., Whitley, D., Burke, E.: The multi-funnel structure of TSP fitness landscapes: a visual exploration. In: EA 2015. LNCS. Springer (2015, to appear)

    Google Scholar 

  20. Ochoa, G., Verel, S., Daolio, F., Tomassini, M.: Local optima networks: a new model of combinatorial fitness landscapes. In: Richter, H., Engelbrecht, A. (eds.) Recent Advances in the Theory and Application of Fitness Landscapes. ECC, vol. 6, pp. 245–276. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  21. Reeves, C.R.: Landscapes, operators and heuristic search. Ann. Oper. Res. 86, 473–490 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  22. Reinelt, G.: TSPLIB - A traveling salesman problem library. ORSA J. Comput. 3(4), 376–384 (1991). http://www.iwr.uni-heidelberg.de/groups/comopt/software/TSPLIB95/

    Article  MathSciNet  MATH  Google Scholar 

  23. Verel, S., Ochoa, G., Tomassini, M.: Local optima networks of NK landscapes with neutrality. IEEE Trans. Evol. Comput. 15(6), 783–797 (2011)

    Article  Google Scholar 

  24. Whitley, D., Hains, D., Howe, A.: Tunneling between optima: partition crossover for the traveling salesman problem. In: Proceedings Genetic and Evolutionary Computation Conference, GECCO 2009, pp. 915–922. ACM, New York (2009)

    Google Scholar 

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Acknowledgements

Thanks are due to Darrell Whitley for relevant discussions and suggesting the paper’s title. This work was supported by the UK’s Engineering and Physical Sciences Research Council [grant number EP/J017515/1].

Data Access. All data generated during this research are openly available from the Stirling Online Repository for Research Data (http://hdl.handle.net/11667/71). All data generated during this research are openly available from the Stirling Online Repository for Research Data (http://hdl.handle.net/11667/71).

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Correspondence to Gabriela Ochoa .

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Ochoa, G., Veerapen, N. (2016). Deconstructing the Big Valley Search Space Hypothesis. In: Chicano, F., Hu, B., García-Sánchez, P. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2016. Lecture Notes in Computer Science(), vol 9595. Springer, Cham. https://doi.org/10.1007/978-3-319-30698-8_5

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  • DOI: https://doi.org/10.1007/978-3-319-30698-8_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30697-1

  • Online ISBN: 978-3-319-30698-8

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