| 書(shū)目名稱 | Large-scale Optimization | | 副標(biāo)題 | Problems and Methods | | 編輯 | Vladimir Tsurkov | | 視頻video | http://file.papertrans.cn/582/581429/581429.mp4 | | 叢書(shū)名稱 | Applied Optimization | | 圖書(shū)封面 |  | | 描述 | Decomposition methods aim to reduce large-scale problems tosimpler problems. This monograph presents selected aspects of thedimension-reduction problem. Exact and approximate aggregations ofmultidimensional systems are developed and from a known model ofinput-output balance, aggregation methods are categorized. The issuesof loss of accuracy, recovery of original variables (disaggregation),and compatibility conditions are analyzed in detail. The method ofiterative aggregation in large-scale problems is studied. For fixedweights, successively simpler aggregated problems are solved and theconvergence of their solution to that of the original problem isanalyzed. An introduction to block integer programming is considered.Duality theory, which is widely used in continuous block programming,does not work for the integer problem. A survey of alternative methodsis presented and special attention is given to combined methods ofdecomposition. Block problems in which the coupling variables do notenter the binding constraints are studied. These models are worthwhilebecause they permit a decomposition with respect to primal and dualvariables by two-level algorithms instead of three-level algorit | | 出版日期 | Book 2001 | | 關(guān)鍵詞 | algorithm; algorithms; model; operations research; optimal control; optimization; programming | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4757-3243-6 | | isbn_softcover | 978-1-4419-4848-9 | | isbn_ebook | 978-1-4757-3243-6Series ISSN 1384-6485 | | issn_series | 1384-6485 | | copyright | Springer Science+Business Media Dordrecht 2001 |
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