This book gives a computationally oriented comparison of solution algorithms for two stage and for jointly chance constrained stochastic linear programming problems. The first part of the book introduces the algorithms including a unified approach to decomposition methods and their regularized counterparts. The second part deals with the computer implementation of the methods, describes a testing environment based on a model management system, and presents comparative computational results with the various algorithms. This ...
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This book gives a computationally oriented comparison of solution algorithms for two stage and for jointly chance constrained stochastic linear programming problems. The first part of the book introduces the algorithms including a unified approach to decomposition methods and their regularized counterparts. The second part deals with the computer implementation of the methods, describes a testing environment based on a model management system, and presents comparative computational results with the various algorithms. This is the first book that presents comparative computational results with several major stochastic programming solution approaches.
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