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)

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.

Keywords

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

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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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