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European Conference on Genetic Programming

EuroGP 2009: Genetic Programming pp 195–207Cite as

There Is a Free Lunch for Hyper-Heuristics, Genetic Programming and Computer Scientists

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5481))

Abstract

In this paper we prove that in some practical situations, there is a free lunch for hyper-heuristics, i.e., for search algorithms that search the space of solvers, searchers, meta-heuristics and heuristics for problems. This has consequences for the use of genetic programming as a method to discover new search algorithms and, more generally, problem solvers. Furthermore, it has also rather important philosophical consequences in relation to the efforts of computer scientists to discover useful novel search algorithms.

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References

  1. Bader-El-Den, M., Poli, R.: Generating SAT local-search heuristics using a GP hyper-heuristic framework. In: Proceedings of Evolution Artificielle (October 2007)

    Google Scholar 

  2. Bader-El-Den, M.B., Poli, R.: A GP-based hyper-heuristic framework for evolving 3-SAT heuristics. In: Thierens, D., Beyer, H.-G., Bongard, J., Branke, J., Clark, J.A., Cliff, D., Congdon, C.B., Deb, K., Doerr, B., Kovacs, T., Kumar, S., Miller, J.F., Moore, J., Neumann, F., Pelikan, M., Poli, R., Sastry, K., Stanley, K.O., Stutzle, T., Watson, R.A., Wegener, I. (eds.) GECCO 2007: Proceedings of the 9th annual conference on Genetic and evolutionary computation, vol. 2, p. 1749. ACM Press, New York (2007)

    Google Scholar 

  3. Banzhaf, W., Nordin, P., Keller, R.E., Francone, F.D.: Genetic Programming – An Introduction; On the Automatic Evolution of Computer Programs and its Applications. Morgan Kaufmann, San Francisco (1998)

    MATH  Google Scholar 

  4. Burke, E., Kendall, G., Newall, J., Hart, E., Ross, P., Schulenburg, S.: Hyper-heuristics: an emerging direction in modern search technology. In: Glover, F.W., Kochenberger, G.A. (eds.) Handbook of metaheuristics, ch. 16, pp. 457–474. Kluwer Academic Publishers, Boston (2003)

    Chapter  Google Scholar 

  5. Burke, E.K., Hyde, M.R., Kendall, G.: Evolving bin packing heuristics with genetic programming. In: Runarsson, T.P., Beyer, H.-G., Burke, E.K., Merelo-Guervós, J.J., Whitley, L.D., Yao, X. (eds.) PPSN 2006. LNCS, vol. 4193, pp. 860–869. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  6. Burke, E.K., Hyde, M.R., Kendall, G., Woodward, J.: Automatic heuristic generation with genetic programming: evolving a jack-of-all-trades or a master of one. In: Thierens, D., Beyer, H.-G., Bongard, J., Branke, J., Clark, J.A., Cliff, D., Congdon, C.B., Deb, K., Doerr, B., Kovacs, T., Kumar, S., Miller, J.F., Moore, J., Neumann, F., Pelikan, M., Poli, R., Sastry, K., Stanley, K.O., Stutzle, T., Watson, R.A., Wegener, I. (eds.) GECCO 2007: Proceedings of the 9th annual conference on Genetic and evolutionary computation, vol. 2, pp. 1559–1565. ACM Press, New York (2007)

    Google Scholar 

  7. Di Chio, C., Poli, R., Langdon, W.B.: Evolution of force-generating equations for PSO using GP. In: Manzoni, S., Palmonari, M., Sartori, F. (eds.) AI*IA Workshop on Evolutionary Computation, Evoluzionistico GSICE 2005, University of Milan Bicocca, Italy, September 20 (2005)

    Google Scholar 

  8. Fukunaga, A.: Automated discovery of composite SAT variable selection heuristics. In: Proceedings of the National Conference on Artificial Intelligence (AAAI), pp. 641–648 (2002)

    Google Scholar 

  9. Igel, C., Toussaint, M.: On classes of functions for which no free lunch results hold. Information Processing Letters 86(6), 317–321 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  10. Igel, C., Toussaint, M.: A no-free-lunch theorem for non-uniform distributions of target functions. Journal of Mathematical Modelling and Algorithms 3, 313–322 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  11. Keller, R.E., Poli, R.: Cost-benefit investigation of a genetic-programming hyperheuristic. In: Monmarché, N., Talbi, E.-G., Collet, P., Schoenauer, M., Lutton, E. (eds.) EA 2007. LNCS, vol. 4926, pp. 13–24. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  12. Keller, R.E., Poli, R.: Linear genetic programming of metaheuristics. In: Thierens, D., Beyer, H.-G., Bongard, J., Branke, J., Clark, J.A., Cliff, D., Congdon, C.B., Deb, K., Doerr, B., Kovacs, T., Kumar, S., Miller, J.F., Moore, J., Neumann, F., Pelikan, M., Poli, R., Sastry, K., Stanley, K.O., Stutzle, T., Watson, R.A., Wegener, I. (eds.) GECCO 2007: Proceedings of the 9th annual conference on Genetic and evolutionary computation, p. 1753. ACM Press, New York (2007)

    Google Scholar 

  13. Keller, R.E., Poli, R.: Linear genetic programming of parsimonious metaheuristics. In: Proceedings of IEEE Congress on Evolutionary Computation (CEC) (September 2007)

    Google Scholar 

  14. Kibria, R.H., Li, Y.: Optimizing the initialization of dynamic decision heuristics in DPLL SAT solvers using genetic programming. In: Collet, P., Tomassini, M., Ebner, M., Gustafson, S., Ekárt, A. (eds.) EuroGP 2006. LNCS, vol. 3905, pp. 331–340. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  15. Koza, J.R.: Genetic Programming: On the Programming of Computers by Natural Selection. MIT Press, Cambridge (1992)

    MATH  Google Scholar 

  16. Oltean, M.: Evolving evolutionary algorithms for function optimization. In: Chen, K. (ed.) The 7th Joint Conference on Information Sciences, September 2003, vol. 1, pp. 295–298. Association for Intelligent Machinery (2003)

    Google Scholar 

  17. Oltean, M.: Evolving evolutionary algorithms using linear genetic programming. Evolutionary Computation 13(3), 387–410 (Fall 2005)

    Article  Google Scholar 

  18. Oltean, M., Dumitrescu, D.: Evolving TSP heuristics using multi expression programming. In: Bubak, M., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2004. LNCS, vol. 3037, pp. 670–673. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  19. Poli, R., Di Chio, C., Langdon, W.B.: Exploring extended particle swarms: a genetic programming approach. In: Beyer, H.-G., O’Reilly, U.-M., Arnold, D.V., Banzhaf, W., Blum, C., Bonabeau, E.W., Cantu-Paz, E., Dasgupta, D., Deb, K., Foster, J.A., de Jong, E.D., Lipson, H., Llora, X., Mancoridis, S., Pelikan, M., Raidl, G.R., Soule, T., Tyrrell, A.M., Watson, J.-P., Zitzler, E. (eds.) GECCO 2005: Proceedings of the 2005 conference on Genetic and evolutionary computation, vol. 1, pp. 169–176. ACM Press, New York (2005)

    Google Scholar 

  20. Poli, R., Langdon, W.B., Holland, O.: Extending particle swarm optimisation via genetic programming. In: Keijzer, M., Tettamanzi, A.G.B., Collet, P., van Hemert, J., Tomassini, M. (eds.) EuroGP 2005. LNCS, vol. 3447, pp. 291–300. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  21. Poli, R., Langdon, W.B., McPhee, N.F.: A field guide to genetic programming (2008), http://lulu.com http://www.gp-field-guide.org.uk (With contributions by Koza, J.R.)

  22. Poli, R., Woodward, J., Burke, E.K.: A histogram-matching approach to the evolution of bin-packing strategies. In: Proceedings of the IEEE Congress on Evolutionary Computation, Singapore (2007) (accepted)

    Google Scholar 

  23. Schumacher, C., Vose, M.D., Whitley, L.D.: The no free lunch and problem description length. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pp. 565–570. Morgan Kaufmann, San Francisco (2001)

    Google Scholar 

  24. Valsecchi, A., Vanneschi, L.: A study of some implications of the no free lunch theorem. In: Giacobini, M., Brabazon, A., Cagnoni, S., Di Caro, G.A., Drechsler, R., Ekárt, A., Esparcia-Alcázar, A.I., Farooq, M., Fink, A., McCormack, J., O’Neill, M., Romero, J., Rothlauf, F., Squillero, G., Uyar, A.Ş., Yang, S. (eds.) EvoWorkshops 2008. LNCS, vol. 4974, pp. 633–642. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  25. Whitley, D., Watson, J.P.: Complexity theory and the no free lunch theorem. In: Burke, E.K., Kendall, G. (eds.) Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques, ch. 11, pp. 317–339. Springer, US (2005)

    Chapter  Google Scholar 

  26. Wolpert, D., Macready, W.: No free lunch theorems for optimization. IEEE Transactions on Evolutionary Computation 1(1), 67–82 (1997)

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Computer Science and Electronic Engineering, University of Essex, UK

    Riccardo Poli & Mario Graff

Authors
  1. Riccardo Poli
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  2. Mario Graff
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Editor information

Editors and Affiliations

  1. Department of Informatics, Systems and Communication (D.I.S.Co.), University of Milano-Bicocca, viale Sarca 336-U14, 20126, Milano, Italy

    Leonardo Vanneschi

  2. GE Global Research, NY 12309, Niskayuna, USA

    Steven Gustafson

  3. Department of Computer Engineering, University of Coimbra, Polo II - Pinhal de Marrocos, 3030, Coimbra, Portugal

    Alberto Moraglio

  4. Institute of High Performance Computing and Networking, National Research Council of Italy (ICAR - CNR), Via P. Castellino 111, 80131, Napoli, Italy

    Ivanoe De Falco

  5. Wilhelm Schickard Institut für Informatik, Eberhard Karls Universität Tübingen, Abt. Rechnerarchitektur, Sand 1, 72076, Tübingen, Germany

    Marc Ebner

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Poli, R., Graff, M. (2009). There Is a Free Lunch for Hyper-Heuristics, Genetic Programming and Computer Scientists. In: Vanneschi, L., Gustafson, S., Moraglio, A., De Falco, I., Ebner, M. (eds) Genetic Programming. EuroGP 2009. Lecture Notes in Computer Science, vol 5481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01181-8_17

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  • DOI: https://doi.org/10.1007/978-3-642-01181-8_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01180-1

  • Online ISBN: 978-3-642-01181-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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