SHAPE - A stochastic hybrid approximation procedure for two-stage stochastic programs
成果类型：
Article
署名作者：
Cheung, RKM; Powell, WB
署名单位：
Hong Kong University of Science & Technology; Princeton University
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.48.1.73.12452
发表日期：
2000
页码：
73-79
关键词：
摘要：
We consider the problem of approximating the expected recourse function for two-stage stochastic programs. Our problem is motivated by applications that have special structure, such as an underlying network that allows reasonable approximations to the expected recourse function to be developed. In this paper, we show how these approximations can be improved by combining them with sample gradient information from the hue recourse function. For the case of strictly convex nonlinear approximations, we prove convergence for this hybrid approximation. The method is attractive for practical reasons because it retains the structure of the approximation.