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Parallel Scalable Algorithms with Mixed Local-Global Strategy for Global Optimization Problems

  • Konstantin Barkalov
  • Vasily Ryabov
  • Sergey Sidorov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6083)

Abstract

This paper continues development of information-statistical approach to minimization of multiextremal functions in the case of non-convex constraints. Proposed approach is called index method. Solving multidimensional problem is reduced to solving equivalent single dimensional one. Dimension reduction is based on Peano curves that allow mapping multidimensional hyper cube onto the segment on real axis. We also use rotating Peano curves that allowed effectively parallelize algorithm to use hundreds of processors. Special attention was paid to mixed local-global strategy for algorithm convergence acceleration.

Keywords

global optimization parallel computing index method local-global strategy 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Konstantin Barkalov
    • 1
  • Vasily Ryabov
    • 1
  • Sergey Sidorov
    • 1
  1. 1.Nizhni Novgorod State UniversityNizhni NovgorodRussia

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