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Modeling with Stochastic Programming [electronic resource] / by Alan J. King, Stein W. Wallace.

By: King, Alan J [author.].
Contributor(s): Wallace, Stein W [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Springer Series in Operations Research and Financial Engineering: Publisher: New York, NY : Springer New York : Imprint: Springer, 2012Description: XVI, 173 p. 30 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9780387878171.Subject(s): Mathematics | Numerical analysis | Mathematical optimization | Distribution (Probability theory) | Operations research | Mathematics | Probability Theory and Stochastic Processes | Operation Research/Decision Theory | Optimization | Numerical AnalysisDDC classification: 519.2 Online resources: Click here to access online
Contents:
Uncertainty in Optimization.-Modeling Feasibility and Dynamics.-Modeling the Objective Function -- Scenario tree generation, With Michal Kaut.-Service network design, With Arnt-Gunnar Lium and Teodor Gabriel Crainic -- A multi-dimensional newsboy problem with substitution, With Hajnalka Vaagen -- Stochastic Discount Factors -- Long Lead Time Production, With Aliza Heching -- References -- Index<.
In: Springer eBooksSummary: While there are several texts on how to solve and analyze stochastic programs, this is the first text to address basic questions about how to model uncertainty, and how to reformulate a deterministic model so that it can be analyzed in a stochastic setting. This text would be suitable as a  stand-alone or supplement for a second course in OR/MS or in optimization-oriented engineering disciplines where the instructor wants to explain where models come from and what the fundamental issues are. The book is easy-to-read,  highly illustrated with lots of examples and discussions. It will be suitable for graduate students and researchers working in operations research, mathematics, engineering and related departments where there is interest in learning how to model uncertainty.   Alan King is a Research Staff Member at IBM's Thomas J. Watson Research Center in New York. Stein W. Wallace is a Professor of Operational Research at Lancaster University Management School in England.  
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Uncertainty in Optimization.-Modeling Feasibility and Dynamics.-Modeling the Objective Function -- Scenario tree generation, With Michal Kaut.-Service network design, With Arnt-Gunnar Lium and Teodor Gabriel Crainic -- A multi-dimensional newsboy problem with substitution, With Hajnalka Vaagen -- Stochastic Discount Factors -- Long Lead Time Production, With Aliza Heching -- References -- Index<.

While there are several texts on how to solve and analyze stochastic programs, this is the first text to address basic questions about how to model uncertainty, and how to reformulate a deterministic model so that it can be analyzed in a stochastic setting. This text would be suitable as a  stand-alone or supplement for a second course in OR/MS or in optimization-oriented engineering disciplines where the instructor wants to explain where models come from and what the fundamental issues are. The book is easy-to-read,  highly illustrated with lots of examples and discussions. It will be suitable for graduate students and researchers working in operations research, mathematics, engineering and related departments where there is interest in learning how to model uncertainty.   Alan King is a Research Staff Member at IBM's Thomas J. Watson Research Center in New York. Stein W. Wallace is a Professor of Operational Research at Lancaster University Management School in England.  

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