Stochastic Linear Programming Algorithms (Hardcover)

Janos Mayer

ISBN 10: 9056991442 / ISBN 13: 9789056991449

Editore: Taylor & Francis Ltd, London, 1998

Hardcover. 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. A computationally oriented comparison of solution algorithms for two stage and jointly chance constrained stochastic linear programming problems, this resource presents comparative computational results with several major stochastic programming solution approaches. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Codice articolo 9789056991449

Riassunto:

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.

Informazioni sull'autore: Janos Mayer

Dati bibliografici

Titolo: Stochastic Linear Programming Algorithms (...
Casa editrice: Taylor & Francis Ltd, London
Data di pubblicazione: 1998
Legatura: Hardcover
Condizione: new
Edizione: prima edizione