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Hybrid Metaheuristics in Combinatorial Optimization: A Tutorial

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Book cover Theory and Practice of Natural Computing (TPNC 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7505))

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Abstract

This article is about a tutorial on hybrid metaheuristics which was given at the first edition of the conference Theory and Practice of Natural Computing, held in October 2012 in Tarragona, Spain. Hybrid metaheuristics are techniques for (combinatorial) optimization that result from a combination of algorithmic components originating from different optimization methods. The tutorial covers five representative examples: (1) the extension of iterated local search towards population-based optimization, (2) the introduction of elements from constraint programming into ant colony optimization, (3) the integration of branch & bound into variable neighborhood search, (4) the use of problem relaxation for guiding tabu search, and (5) the combination of dynamic programming with evolutionary algorithms.

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References

  1. Bertsekas, D.P.: Dynamic Programming and Optimal Control, 3rd edn. Athena Scientific, Nashua (2007)

    Google Scholar 

  2. Blum, C.: Revisiting dynamic programming for finding optimal subtrees in trees. European Journal of Operational Research 177(1), 102–115 (2007)

    Article  MATH  Google Scholar 

  3. Blum, C., Blesa, M.J.: Solving the KCT problem: Large-scale neighborhood search and solution merging. In: Alba, E., Blum, C., Isasi, P., León, C., Gómez, J.A. (eds.) Optimization Techniques for Solving Complex Problems, pp. 407–421. Wiley & Sons, Hoboken (2009)

    Chapter  Google Scholar 

  4. Blum, C., Blesa Aguilera, M.J., Roli, A., Sampels, M. (eds.): Hybrid Metaheuristics – An Emerging Approach to Optimization. SCI, vol. 114. Springer, Berlin (2008)

    MATH  Google Scholar 

  5. Blum, C., Puchinger, J., Raidl, G., Roli, A.: Hybrid metaheuristics in combinatorial optimization: A survey. Applied Soft Computing 11(6), 4135–4151 (2011)

    Article  Google Scholar 

  6. Blum, C., Roli, A.: Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Computing Surveys 35(3), 268–308 (2003)

    Article  Google Scholar 

  7. Cotta, C.: A study of hybridisation techniques and their application to the design of evolutionary algorithms. AI Communications 11(3-4), 223–224 (1998)

    Google Scholar 

  8. Dorigo, M., Stützle, T.: Ant Colony Optimization. MIT Press, Cambridge (2004)

    Book  MATH  Google Scholar 

  9. Dumitrescu, I., Stützle, T.: Combinations of Local Search and Exact Algorithms. In: Raidl, G.R., Cagnoni, S., Cardalda, J.J.R., Corne, D.W., Gottlieb, J., Guillot, A., Hart, E., Johnson, C.G., Marchiori, E., Meyer, J.-A., Middendorf, M. (eds.) EvoWorkshops 2003. LNCS, vol. 2611, pp. 211–223. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  10. Glover, F., Kochenberger, G. (eds.): Handbook of Metaheuristics. International Series in Operations Research & Management Science, vol. 57. Kluwer Academic Publishers (2003)

    Google Scholar 

  11. Hansen, P., Mladenovic, N., Brimberg, J., Moreno Pérez, J.A.: Variable neighborhood search. In: Gendreau, M., Potvin, J.Y. (eds.) Handbook of Metaheuristics, 2nd edn. International Series in Operations Research & Management Science, vol. 146, pp. 61–86. Springer, Berlin (2010)

    Chapter  Google Scholar 

  12. Jourdan, L., Basseur, M., Talbi, E.: Hybridizing exact methods and metaheuristics: A taxonomy. European Journal of Operational Research 199(3), 620–629 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  13. Lourenço, H.R., Martin, O., Stützle, T.: Iterated local search. In: Glover, F., Kochenberger, G. (eds.) Handbook of Metaheuristics. International Series in Operations Research & Management Science, vol. 57, pp. 321–353. Kluwer Academic Publishers, Norwell (2002)

    Google Scholar 

  14. Maniezzo, V., Stützle, T., Voß, S. (eds.): Matheuristics. Annals of Information Systems, vol. 10. Springer, Berlin (2010)

    Google Scholar 

  15. Marriott, K., Stuckey, P.J.: Introduction to Constraint Logic Programming. MIT Press, Cambridge (1998)

    Google Scholar 

  16. Meyer, B.: Hybrids of constructive meta-heuristics and constraint programming: A case study with ACO. In: Blum, et al. [4], vol. 114, ch. 6, pp. 151–183 (2008)

    Google Scholar 

  17. Pesant, G., Gendreau, M.: A Constraint Programming Framework for Local Search Methods. Journal of Heuristics 5, 255–279 (1999)

    Article  MATH  Google Scholar 

  18. Pisinger, D., Ropke, S.: Large neighborhood search. In: Gendreau, M., Potvin, J.Y. (eds.) Handbook of Metaheuristics, 2nd edn. International Series in Operations Research & Management Science, vol. 146, pp. 399–419. Springer, Berlin (2010)

    Chapter  Google Scholar 

  19. Raidl, G.R.: A Unified View on Hybrid Metaheuristics. In: Almeida, F., Blesa Aguilera, M.J., Blum, C., Moreno Vega, J.M., Pérez Pérez, M., Roli, A., Sampels, M. (eds.) HM 2006. LNCS, vol. 4030, pp. 1–12. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  20. Raidl, G.R., Puchinger, J., Blum, C.: Metaheuristic hybrids. In: Gendreau, M., Potvin, J.Y. (eds.) Handbook of Metaheuristics, 2nd edn. International Series in Operations Research & Management Science, vol. 146, pp. 469–496. Springer, Berlin (2010)

    Chapter  Google Scholar 

  21. Reeves, C.R. (ed.): Modern heuristic techniques for combinatorial problems. John Wiley & Sons, New York (1993)

    MATH  Google Scholar 

  22. Roli, A., Benedettini, S., Stützle, T., Blum, C.: Large neighbourhood search algorithms for the founder sequence reconstruction problem. Computers & Operations Research 39(2), 213–224 (2012)

    Article  MathSciNet  Google Scholar 

  23. Solnon, C.: Ant Colony Optimization and Constraint Programming. Wiley-ISTE (2010)

    Google Scholar 

  24. Stützle, T.: Local Search Algorithms for Combinatorial Problems - Analysis, Algorithms and New Applications. DISKI - Dissertationen zur Künstlichen Intelligenz, Infix, Sankt Augustin, Germany (1999)

    Google Scholar 

  25. Stützle, T.: Iterated local search for the quadratic assignment problem. European Journal of Operational Research 174(3), 1519–1539 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  26. Vasquez, M., Hao, J.K.: A hybrid approach for the 0–1 multidimensional knapsack problem. In: Nebel, B. (ed.) Proceedings of the 17th International Joint Conference on Artificial Intelligence, IJCAI 2001, pp. 328–333. Morgan Kaufman, Seattle (2001)

    Google Scholar 

  27. Vasquez, M., Vimont, Y.: Improved results on the 0–1 multidimensional knapsack problem. European Journal of Operational Research 165(1), 70–81 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  28. Wu, Y., Gusfield, D.: Improved Algorithms for Inferring the Minimum Mosaic of a Set of Recombinants. In: Ma, B., Zhang, K. (eds.) CPM 2007. LNCS, vol. 4580, pp. 150–161. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

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Author information

Authors and Affiliations

  1. ALBCOM Research Group, Universitat Politécnica de Catalunya, c/ Jordi Girona 1-3, Barcelona, Spain

    Christian Blum

Authors
  1. Christian Blum
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Editor information

Editors and Affiliations

  1. Research Group on Mathematical Linguistics, Universitat Rovira i Virgili, Avinguda Catalunya, 35, 43002, Tarragona, Spain

    Adrian-Horia Dediu  & Carlos Martín-Vide  & 

  2. Fakultät für Informatik, Otto-von-Guericke-Universität Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany

    Bianca Truthe

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Blum, C. (2012). Hybrid Metaheuristics in Combinatorial Optimization: A Tutorial. In: Dediu, AH., Martín-Vide, C., Truthe, B. (eds) Theory and Practice of Natural Computing. TPNC 2012. Lecture Notes in Computer Science, vol 7505. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33860-1_1

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  • DOI: https://doi.org/10.1007/978-3-642-33860-1_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33859-5

  • Online ISBN: 978-3-642-33860-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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