Stochastic Programming Modeling

Monday, August 8, 2016 - 9:00am - 10:30am
Lind 305
Jeff Linderoth (University of Wisconsin, Madison)
This lecture gives an introduction to modeling optimization
problems where parameters of the problem are uncertain. The primary
focus will be on the case when the uncertain parameters are modeled as
random variables. We will introduce both two-stage, recourse-based
stochastic programming and chance-constrained approaches. Statistics
that measure the value of computing a solution to the stochastic
problem will be introduced. We will show how to create
an equivalent extensive form formulations of the instances, so that
they may be solved with standard optimization software.
MSC Code: