A computationally oriented comparison of solution algorithms for two stage and jointly chance constrained stochastic linear programming problems, this is the first book to present comparative computational results with several major stochastic programming solution approaches. The following methods are considered: regularized decomposition, stochastic decomposition and successive discrete approximation methods for two stage problems; cutting plane methods, and a reduced gradient method for jointly chance constrained problems. The first part of the book introduces the algorithms, including a unified approach to decomposition methods and their regularized counterparts. The second part addresses computer implementation of the methods, describes a testing environment based on a model management system, and presents comparative computational results with the various algorithms. Emphasis is on the computational behavior of the algorithms.
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Janos Mayer
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Da: Der Buchfreund, Wien, Austria
Original-Pappband. Condizione: Sehr gut. 4 Original-Pappband en Mathematik, Naturwissenschaften (Optimization Theory and Applications. Vol. 1); IX pp., 153 pp. Codice articolo 1057
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Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. pp. 163 This item is printed on demand. Codice articolo 5671041
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Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. pp. 163 1st Edition. Codice articolo 262176862
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Da: Biblios, Frankfurt am main, HESSE, Germania
Condizione: New. pp. 163. Codice articolo 182176852
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Da: moluna, Greven, Germania
Condizione: New. Janos MayerA computationally oriented comparison of solution algorithms for two stage and jointly chance constrained stochastic linear programming problems, this is the first book to present comparative computational results with several major stochasti. Codice articolo 599121754
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Da: AHA-BUCH GmbH, Einbeck, Germania
Buch. Condizione: Neu. Neuware - A computationally oriented comparison of solution algorithms for two stage and jointly chance constrained stochastic linear programming problems, this is the first book to present comparative computational results with several major stochastic programming solution approaches.The following methods are considered: regularized decomposition, stochastic decomposition and successive discrete approximation methods for two stage problems; cutting plane methods, and a reduced gradient method for jointly chance constrained problems.The first part of the book introduces the algorithms, including a unified approach to decomposition methods and their regularized counterparts. The second part addresses computer implementation of the methods, describes a testing environment based on a model management system, and presents comparative computational results with the various algorithms. Emphasis is on the computational behavior of the algorithms. Codice articolo 9789056991449
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