Barycentric Bounds in Stochastic Programming: Theory and Application [chapter]

Karl Frauendorfer, Daniel Kuhn, Michael Schürle
2010 International Series in Operations Research and Management Science  
The design and analysis of efficient approximation schemes is of fundamental importance in stochastic programming research. Bounding approximations are particularly popular for providing strict error bounds that can be made small by using partitioning techniques. In this article we develop a powerful bounding method for linear multistage stochastic programs with a generalized nonconvex dependence on the random parameters. Thereby, we establish bounds on the recourse functions as well as compact
more » ... bounding sets for the optimal decisions. We further demonstrate that our bounding methods facilitate the reliable solution of important real-life decision problems. To this end, we solve a stochastic optimization model for the management of non-maturing accounts and compare the bounds on maximum profit obtained with different partitioning strategies.
doi:10.1007/978-1-4419-1642-6_5 fatcat:mjga36jpx5dvfahayedenyawza