Sublinear upper bounds for stochastic programs with recourse

Sublinear upper bounds for stochastic programs with recourse

Separable sublinear functions are used to provide upper bounds on the recourse function of a stochastic program. The resulting problem's objective involves the inf-convolution of convex functions. A dual of this problem is formulated to obtain an implementable procedure to calculate the bound. Function evaluations for the resulting convex program only require a small number of single integratio...

Stochastic Programs with Recourse

Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/page/info/about/policies/terms.jsp. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive o...

Stochastic Programs with Recourse: Upper bounds and Moment Problems∗ - A Review -

Upper bounds for Gaussian stochastic programs

We present a construction which gives deterministic upper bounds for stochastic programs in which the randomness appears on the right{hand{side and has a multivariate Gaussian distribution. Computation of these bounds requires the solution of only as many linear programs as the problem has variables.

A Stochastic Newton Method for Stochastic Quadratic Programs with Recourse

In this paper, we combine the inexact Newton method with the stochastic decomposition method and present a stochastic Newton method for solving the two-stage stochastic program. We prove that the new method is superlinearly convergent with probability one and a probabilistic error bound h(N k). The error bound h(N k) at least has the same order as jjy k ?y jj when k ! 1. In the algorithm, we ca...