A stochastic programming model to find optimal sample sizes to estimate unknown parameters in an LP

作     者：Prékopa, A Hou, XL 

作者机构：Rutgers State Univ RUTCOR Ctr Operat Res Piscataway NJ 08854 USA 

出 版 物：《OPERATIONS RESEARCH LETTERS》 (运筹学快报)

年 卷 期：2004年第32卷第1期

页      面：59-67页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070104[理学-应用数学] 0701[理学-数学] 

主　　题：stochastic programming confidence interval logconcavity game theory 

摘      要：An LP is considered where the technology coefficients are unknown and random samples are taken to estimate them. A stochastic programming problem is formulated to find the optimal sample sizes where it is required that a confidence interval should cover the unknown deterministic optimum value by a given probability and the cost of sampling be minimum. (C) 2003 Elsevier B.V. All rights reserved.