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Hybrid Metaheuristics for the Far From Most String Problem

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Hybrid Metaheuristics (HM 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7919))

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Abstract

Among the sequence selection and comparison problems, the Far From Most String Problem (FFMSP) is one of the computationally hardest with applications in several fields, including molecular biology where one is interested in creating diagnostic probes for bacterial infections or in discovering potential drug targets.

In this article, several hybrid metaheuristics are described and tested. Extensive comparative experiments on a large set of randomly generated test instances indicate that these randomized hybrid techniques are both effective and efficient.

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References

  1. Aiex, R.M., Resende, M.G.C., Ribeiro, C.C.: Probability distribution of solution time in GRASP: an experimental investigation. Journal of Heuristics 8, 343–373 (2002)

    Article  MATH  Google Scholar 

  2. Canuto, S.A., Resende, M.G.C., Ribeiro, C.C.: Local search with perturbations for the prize-collecting Steiner tree problem in graphs. Networks 38, 50–58 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  3. Feo, T.A., Resende, M.G.C.: A probabilistic heuristic for a computationally difficult set covering problem. Oper. Res. Lett. 8, 67–71 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  4. Feo, T.A., Resende, M.G.C.: Greedy randomized adaptive search procedures. J. Global Optim. 6, 109–133 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  5. Festa, P.: On some optimization problems in mulecolar biology. Mathematical Bioscience 207(2), 219–234 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  6. Festa, P., Pardalos, P.M., Pitsoulis, L.S., Resende, M.G.C.: GRASP with path-relinking for the weighted MAXSAT problem. ACM J. of Experimental Algorithmics 11, 1–16 (2006)

    MathSciNet  Google Scholar 

  7. Festa, P., Pardalos, P.M., Resende, M.G.C., Ribeiro, C.C.: Randomized heuristics for the MAX-CUT problem. Optimization Methods and Software 7, 1033–1058 (2002)

    Article  MathSciNet  Google Scholar 

  8. Festa, P., Resende, M.G.C.: GRASP: An annotated bibliography. In: Ribeiro, C.C., Hansen, P. (eds.) Essays and Surveys on Metaheuristics, pp. 325–367. Kluwer Academic Publishers (2002)

    Google Scholar 

  9. Festa, P., Resende, M.G.C.: An annotated bibliography of GRASP – Part I: Algorithms. International Transactions in Operational Research 16(1), 1–24 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  10. Festa, P., Resende, M.G.C.: An annotated bibliography of GRASP – Part II: Applications. International Transactions in Operational Research 16(2), 131–172 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  11. Frances, M., Litman, A.: On covering problems of codes. Theory of Computing Systems 30(2), 113–119 (1997)

    MathSciNet  MATH  Google Scholar 

  12. Glover, F.: Tabu search and adaptive memory programing – Advances, applications and challenges. In: Barr, R.S., Helgason, R.V., Kennington, J.L. (eds.) Interfaces in Computer Science and Operations Research, pp. 1–75. Kluwer (1996)

    Google Scholar 

  13. Glover, F.: Multi-start and strategic oscillation methods – Principles to exploit adaptive memory. In: Laguna, M., Gonzáles-Velarde, J.L. (eds.) Computing Tools for Modeling, Optimization and Simulation: Interfaces in Computer Science and Operations Research, pp. 1–24. Kluwer (2000)

    Google Scholar 

  14. Glover, F., Laguna, M.: Tabu search. Kluwer Academic Publishers (1997)

    Google Scholar 

  15. Glover, F., Laguna, M., Martí, R.: Fundamentals of scatter search and path relinking. Control and Cybernetics 39, 653–684 (2000)

    Google Scholar 

  16. Hansen, P., Mladenović, N.: Developments of variable neighborhood search. In: Ribeiro, C.C., Hansen, P. (eds.) Essays and Surveys in Metaheuristics, pp. 415–439. Kluwer Academic Publishers (2002)

    Google Scholar 

  17. Laguna, M., Martí, R.: GRASP and path relinking for 2-layer straight line crossing minimization. INFORMS J. on Computing 11, 44–52 (1999)

    Article  MATH  Google Scholar 

  18. Lanctot, J., Li, M., Ma, B., Wang, S., Zhang, L.: Distinguishing string selection problems. Information and Computation 185(1), 41–55 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  19. Meneses, C.N., Oliveira, C.A.S., Pardalos, P.M.: Optimization techniques for string selection and comparison problems in genomics. IEEE Engineering in Medicine and Biology Magazine 24(3), 81–87 (2005)

    Article  Google Scholar 

  20. Mousavi, S.R., Babaie, M., Montazerian, M.: An improved heuristic for the far from most strings problem. Journal of Heuristics 18, 239–262 (2012)

    Article  Google Scholar 

  21. Ribeiro, C.C., Rosseti, I., Vallejos, R.: Exploiting run time distributions to compare sequential and parallel stochastic local search algorithms. Journal of Global Optimization 54, 405–429 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  22. Sim, J.S., Park, K.: The consensus string problem for a metric is NP-complete. In: Proceedings of the Annual Australiasian Workshop on Combinatorial Algorithms (AWOCA), pp. 107–113 (1999)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Mathematics and Applications ‘‘R. Caccioppoli’’, University of Napoli FEDERICO II, Italy

    Daniele Ferone & Paola Festa

  2. AT&T Labs Research, Florham Park, NJ, USA

    Mauricio G. C. Resende

Authors
  1. Daniele Ferone
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  2. Paola Festa
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  3. Mauricio G. C. Resende
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Editor information

Editors and Affiliations

  1. Universitat Politècnica de Catalunya, Omega 213 Campus Nord, Jordi Girona 1-3, 08034, Barcelona, Spain

    María J. Blesa

  2. IKERBASQUE, Basque Foundation for Science, Department of Computer Science and Artificial Intelligence, University of the Basque Country, Paseo Manuel Lardizabal 1, 20018, San Sebastian, Spain

    Christian Blum

  3. Department of Mathematics and Applications “R. Caccioppoli”, Compl. M.S.A., University of Naples Federico II, Via Cintia, 80126, Naples, Italy

    Paola Festa

  4. DISI, Università di Bologna, Campus of Cesena, Via Venezia 52, 47521, Cesena, Italy

    Andrea Roli

  5. IRIDIA CP 194/6, Université Libre de Bruxelles, Avenue Franklin D. Roosevelt 50, 1050, Bruxelles, Belgium

    Michael Sampels

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© 2013 Springer-Verlag Berlin Heidelberg

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Ferone, D., Festa, P., Resende, M.G.C. (2013). Hybrid Metaheuristics for the Far From Most String Problem. In: Blesa, M.J., Blum, C., Festa, P., Roli, A., Sampels, M. (eds) Hybrid Metaheuristics. HM 2013. Lecture Notes in Computer Science, vol 7919. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38516-2_14

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  • DOI: https://doi.org/10.1007/978-3-642-38516-2_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38515-5

  • Online ISBN: 978-3-642-38516-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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