Parallel Hierarchical Methods for Complex Systems Optimization

  • Ewa Niewiadomska-Szynkiewicz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3980)


The paper is concerned with computational research for large scale systems. The focus is on the hierarchical optimization methods that can be successfully applied to large scale optimization problems. A key issue is the possibility of solving several less dimension problems instead of one global high dimension task. Particular emphasis is laid on coarse granularity parallel implementation and its effectiveness. The paper discusses the usage of price coordination for real-life systems optimization. The results of numerical experiments performed for mean-variance portfolio selection using cluster of computers are presented and discussed.


Optimal Portfolio Portfolio Selection Message Passing Interface Common Resource Price Method 
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 2006

Authors and Affiliations

  • Ewa Niewiadomska-Szynkiewicz
    • 1
    • 2
  1. 1.Institute of Control and Computation EngineeringWarsaw University of TechnologyWarsawPoland
  2. 2.Research and Academic Computer Network (NASK)WarsawPoland

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