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Stochastic Programming - Modeling Decision Problems Under Uncertainty (Hardcover, 1st ed. 2020)
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Stochastic Programming - Modeling Decision Problems Under Uncertainty (Hardcover, 1st ed. 2020)
Series: Graduate Texts in Operations Research
Expected to ship within 10 - 15 working days
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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 to practical problems. The book
is based on lecture notes developed for an Econometrics and
Operations Research course for master students at the University of
Groningen, the Netherlands - the longest-standing Stochastic
Programming course worldwide.
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