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Comparing two probabilistic models of the computational complexity of the branch and bound algorithm

  • Michèle Dion
  • Marc Gengler
  • Stéphane Ubéda
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 854)

Abstract

We study two probabilistic models developed in order to predict the computational complexity of the branch and bound algorithm as well as its suitability for a parallelization based on the simultaneous exploration of all subproblems having a same common lower bound We show that both models, starting from different assumptions, yield asymptotically the same results but differ for small problems. Both models agree to predict a quick increase of the number of subproblems as a function of their lower bounds offering a convenient approach for parallelization of the branch and bound algorithm.

Keywords

Branch and bound algorithm combinatorial optimization complexity modelization parallel computing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • Michèle Dion
    • 1
  • Marc Gengler
    • 2
  • Stéphane Ubéda
    • 3
  1. 1.Laboratoire de l'Informatique du ParallélismeEcole Normale Supérieure - LyonLyonFrance
  2. 2.Laboratoire d'Informatique Théorique, Ecublens (IN)Ecole Polytechnique Fédérale de LausanneLausanneSwitzerland
  3. 3.Laboratoire de Traitement du Signal et InstrumentationUniversité de Saint-EtienneSaint-EtienneFrance

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