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Decomposition Methods Based on Nonsmooth Optimization

  • Naum Z. Shor
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 24)

Abstract

Decomposition methods are used for solving large-scale linear and convex programming problems in order to save time by reducing the number of references to the external memory of a computer. Such methods convert the solution of the original problem into the solution of a series of problems of lower dimension (blocks). They are particularly efficient if the structure of each block permits the use of special, fast solution methods, or the structure of multiprocessor computer permits to make computations simultaneously for many blocks. We shall consider the use of the subgradient-type methods in iterative algorithms for solving linear, convex and some mixed programming problems with the aid of decomposition schemes.

Keywords

Decomposition Method Lagrange Function Transportation Problem Decomposition Scheme Nonsmooth Optimization 
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 Science+Business Media Dordrecht 1998

Authors and Affiliations

  • Naum Z. Shor
    • 1
  1. 1.V.M. Glushkov Institute of CyberneticsUkrainian National Academy of SciencesKievUkraine

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