Description: In an extensively updated new edition, this book teaches stochastic programming, with new approaches for discrete variables, new results on risk measures in modeling and Monte Carlo sampling methods, a new chapter on relationships to other methods and more.
Review Quotes:
From the reviews of the second edition:
"Help the students to understand how to model uncertainty into mathematical optimization problems, what uncertainty brings to the decision process and which techniques help to manage uncertainty in solving the problems. ... certainly attract also the wide spectrum of readers whose main interest lies in possible exploitation of stochastic programming methodology and will help them to find their own way to treat actual problems using stochastic programming methods. As a whole, the three main building blocks of stochastic programming ... are well represented and balanced." (Jitka Dupačová, Zentralblatt MATH, Vol. 1223, 2011)