Hybrid Metaheuristics for the Far From Most String Problem

  • Daniele Ferone
  • Paola Festa
  • Mauricio G. C. Resende
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7919)


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.


Computational biology Molecular structure prediction Protein and sequences alignment Combinatorial optimization Hybrid metaheuristics 


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  1. 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)CrossRefzbMATHGoogle Scholar
  2. 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)MathSciNetCrossRefzbMATHGoogle Scholar
  3. 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)MathSciNetCrossRefzbMATHGoogle Scholar
  4. 4.
    Feo, T.A., Resende, M.G.C.: Greedy randomized adaptive search procedures. J. Global Optim. 6, 109–133 (1995)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Festa, P.: On some optimization problems in mulecolar biology. Mathematical Bioscience 207(2), 219–234 (2007)MathSciNetCrossRefzbMATHGoogle Scholar
  6. 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)MathSciNetGoogle Scholar
  7. 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)MathSciNetCrossRefGoogle Scholar
  8. 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. 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)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 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)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Frances, M., Litman, A.: On covering problems of codes. Theory of Computing Systems 30(2), 113–119 (1997)MathSciNetzbMATHGoogle Scholar
  12. 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. 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. 14.
    Glover, F., Laguna, M.: Tabu search. Kluwer Academic Publishers (1997)Google Scholar
  15. 15.
    Glover, F., Laguna, M., Martí, R.: Fundamentals of scatter search and path relinking. Control and Cybernetics 39, 653–684 (2000)Google Scholar
  16. 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. 17.
    Laguna, M., Martí, R.: GRASP and path relinking for 2-layer straight line crossing minimization. INFORMS J. on Computing 11, 44–52 (1999)CrossRefzbMATHGoogle Scholar
  18. 18.
    Lanctot, J., Li, M., Ma, B., Wang, S., Zhang, L.: Distinguishing string selection problems. Information and Computation 185(1), 41–55 (2003)MathSciNetCrossRefzbMATHGoogle Scholar
  19. 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)CrossRefGoogle Scholar
  20. 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)CrossRefGoogle Scholar
  21. 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)MathSciNetCrossRefzbMATHGoogle Scholar
  22. 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

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Daniele Ferone
    • 1
  • Paola Festa
    • 1
  • Mauricio G. C. Resende
    • 2
  1. 1.Department of Mathematics and Applications ‘‘R. Caccioppoli’’University of Napoli FEDERICO IIItaly
  2. 2.AT&T Labs ResearchFlorham ParkUSA

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