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Record Nr. |
UNINA9910367242103321 |
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Autore |
Klein Haneveld Willem K |
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Titolo |
Stochastic Programming : Modeling Decision Problems Under Uncertainty / / by Willem K. Klein Haneveld, Maarten H. van der Vlerk, Ward Romeijnders |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (255 pages) : illustrations |
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Collana |
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Graduate Texts in Operations Research, , 2662-6012 |
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Disciplina |
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Soggetti |
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Operations research |
Decision making |
Probabilities |
Mathematical optimization |
Economics |
Operations Research/Decision Theory |
Probability Theory and Stochastic Processes |
Optimization |
Economic Theory/Quantitative Economics/Mathematical Methods |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Introduction -- Random Objective Functions -- Recourse Models -- Stochastic Mixed-integer Programming -- Chance Constraints -- Integrated Chance Constraints -- Assignments -- Case Studies. |
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Sommario/riassunto |
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This book provides an essential introduction to Stochastic Programming, especially intended for graduate students. The book begins by exploring a linear programming problem with random parameters, representing a decision problem under uncertainty. Several models for this problem are presented, including the main ones used in Stochastic Programming: recourse models and chance constraint models. The book not only discusses the theoretical properties of these models and algorithms for solving them, but also explains the intrinsic differences between the models. In the book’s closing section, several case studies are presented, helping students apply the theory covered |
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