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Mixed Models for the Analysis of Local Search Components

  • Jørgen Bang-Jensen
  • Marco Chiarandini
  • Yuri Goegebeur
  • Bent Jørgensen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4638)

Abstract

We consider a possible scenario of experimental analysis on heuristics for optimization: identifying the contribution of local search components when algorithms are evaluated on the basis of solution quality attained.

We discuss the experimental designs with special focus on the role of the test instances in the statistical analysis. Contrary to previous practice of modeling instances as a blocking factor, we treat them as a random factor. Together with algorithms, or their components, which are fixed factors, this leads naturally to a mixed ANOVA model. We motivate our choice and illustrate the application of the mixed model on a study of local search for the 2-edge-connectivity problem.

Keywords

Local Search Test Instance Local Search Algorithm Blocking Factor Geometric Random Graph 
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 2007

Authors and Affiliations

  • Jørgen Bang-Jensen
    • 1
  • Marco Chiarandini
    • 1
  • Yuri Goegebeur
    • 2
  • Bent Jørgensen
    • 2
  1. 1.Department of Mathematics and Computer Science, University of Southern Denmark, OdenseDenmark
  2. 2.Department of Statistics, University of Southern Denmark, OdenseDenmark

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