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- DescriptionDecomposition methods aim to reduce large-scale problems to simpler problems. This mograph presents selected aspects of the dimension-reduction problem. Exact and approximate aggregations of multidimensional systems are developed and from a kwn model of input-output balance, aggregation methods are categorized. The issues of loss of accuracy, recovery of original variables (disaggregation), and compatibility conditions are analyzed in detail. The method of iterative aggregation in large-scale problems is studied. For fixed weights, successively simpler aggregated problems are solved and the convergence of their solution to that of the original problem is analyzed. An introduction to block integer programming is considered. Duality theory, which is widely used in continuous block programming, does t work for the integer problem. A survey of alternative methods is presented and special attention is given to combined methods of decomposition. Block problems in which the coupling variables do t enter the binding constraints are studied. These models are worthwhile because they permit a decomposition with respect to primal and dual variables by two-level algorithms instead of three-level algorithms. Audience: This book is addressed to specialists in operations research, optimization, and optimal control.
- Author(s)Vladimir Tsurkov
- PublisherSpringer-Verlag New York Inc.
- Date of Publication08/12/2010
- Series TitleApplied Optimization
- Series Part/Volume Number51
- Place of PublicationNew York, NY
- Country of PublicationUnited States
- ImprintSpringer-Verlag New York Inc.
- Content Note1 black & white illustrations, biography
- Weight498 g
- Width155 mm
- Height235 mm
- Spine17 mm
- Edition Statement1st ed. Softcover of orig. ed. 2001
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