163 pp., Hardcover, very good. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.

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Detalles bibliogr�ficos

T�tulo: Stochastic Linear Programming Algorithms: A Comparison Based on a Model Management System (Optimization Theory & Applications Series Volume 1)
Editor: Gordon and Breach
Fecha de publicaci�n: 1998
Idioma: Ingl�s
ISBN 10: 9056991442
ISBN 13: 9789056991449
Encuadernaci�n: Encuadernaci�n de tapa dura
Estado: Very Good

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Sinopsis

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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