A Math-Heuristic Algorithm for the DNA Sequencing Problem

  • Marco Caserta
  • Stefan Voß
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6073)

Abstract

One of the key issues in designing an algorithm in general, and a metaheuristic in particular, concerns the fine tuning of one or more algorithmic parameters. In this paper, we present a simple mechanism aimed at automatically fine tuning a parameter of a novel hybrid algorithm. We design an algorithm that uses mathematical programming techniques in a metaheuristic fashion and we exploit ideas from the corridor method to drive the use of a standard MIP solver over different portions of the solution space. The size and the boundaries of such portions of the solution space are determined by the width of the corridor built around an incumbent solution. In turn, the corridor width is automatically fine tuned by the proposed mechanism, taking into account the evolution of the search process. The proposed algorithm is then tested on a well known problem from computational biology and results on a set of benchmark instances are provided.

Keywords

Solution Space Benchmark Instance Incumbent Solution Orienteering Problem Short Computational Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Marco Caserta
    • 1
  • Stefan Voß
    • 1
  1. 1.Institute of Information Systems (IWI)University of HamburgHamburgGermany

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