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Global stochastic optimization techniques applied to partitioning

  • Javier Trejos
  • Alex Murillo
  • Eduardo Piza
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

We have applied three global stochastic optimization techniques to the problem of partitioning: simulated annealing, genetic algorithms and tabu search. The criterion to be minimized is the within-variance. Results obtained are compared with those of classical algorithms and are shown to be better in nearly all cases.

Keywords

genetic algorithms simulated annealing tabu search within-variance numerical variables 

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Copyright information

© Springer-Verlag Berlin · Heidelberg 1998

Authors and Affiliations

  • Javier Trejos
    • 1
  • Alex Murillo
    • 1
  • Eduardo Piza
    • 1
  1. 1.PIMAD-CIMPA, School of MathematicsUniversity of Costa RicaSan JoséCosta Rica

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