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Fitness Landscape Based Parameter Estimation for Robust Taboo Search

  • Andreas Beham
  • Erik Pitzer
  • Michael Affenzeller
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8111)

Introduction

Metaheuristic optimization algorithms are general optimization strategies suited to solve a range of real-world relevant optimization problems. Many metaheuristics expose parameters that allow to tune the effort that these algorithms are allowed to make and also the strategy and search behavior [1]. Adjusting these parameters allows to increase the algorithms’ performances with respect to different problem- and problem instance characteristics.

Keywords

Problem Instance Problem Size Fitness Landscape Quadratic Assignment Problem Large Problem Size 
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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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Andreas Beham
    • 1
  • Erik Pitzer
    • 1
  • Michael Affenzeller
    • 1
  1. 1.School of Informatics, Communications and MediaUniversity of Applied Sciences Upper AustriaHagenbergAustria

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