Annals of Operations Research

, Volume 207, Issue 1, pp 27–41 | Cite as

A hyper-heuristic approach to sequencing by hybridization of DNA sequences

  • Jacek Blazewicz
  • Edmund K. Burke
  • Graham Kendall
  • Wojciech Mruczkiewicz
  • Ceyda Oguz
  • Aleksandra Swiercz
Article

Abstract

In this paper we investigate the use of hyper-heuristic methodologies for predicting DNA sequences. In particular, we utilize Sequencing by Hybridization. We believe that this is the first time that hyper-heuristics have been investigated in this domain. A hyper-heuristic is provided with a set of low-level heuristics and the aim is to decide which heuristic to call at each decision point. We investigate three types of hyper-heuristics. Two of these (simulated annealing and tabu search) draw their inspiration from meta-heuristics. The choice function hyper-heuristic draws its inspiration from reinforcement learning. We utilize two independent sets of low-level heuristics. The first set is based on a previous tabu search method, with the second set being a significant extension to this basic set, including utilizing a different representation and introducing the definition of clusters. The datasets we use comprises two randomly generated datasets and also a publicly available biological dataset. In total, we carried out experiments using 70 different combinations of heuristics, using the three datasets mentioned above and investigating six different hyper-heuristic algorithms. Our results demonstrate the effectiveness of a hyper-heuristic approach to this problem domain. It is necessary to provide a good set of low-level heuristics, which are able to both intensify and diversify the search but this approach has demonstrated very encouraging results on this extremely difficult and important problem domain.

Keywords

Hyper-heuristics Simulated annealing Tabu search Choice function Sequencing by hybridization 

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Jacek Blazewicz
    • 1
    • 2
  • Edmund K. Burke
    • 3
  • Graham Kendall
    • 3
  • Wojciech Mruczkiewicz
    • 1
  • Ceyda Oguz
    • 4
  • Aleksandra Swiercz
    • 1
    • 2
  1. 1.Institute of Computing SciencePoznan University of TechnologyPoznanPoland
  2. 2.Institute of Bioorganic ChemistryPolish Academy of SciencePoznanPoland
  3. 3.School of Computer ScienceUniversity of NottinghamNottinghamUK
  4. 4.Department of Industrial EngineeringKoç UniversityIstanbulTurkey

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