State partitioning based linear program for stochastic dynamic programs: An invariance property

作     者：Park, M. Krishnamoorthy, K. Darbha, S. Chandler, P. Pachter, M. 

作者机构：Infoscitex Corp Technol Solut Div Dayton OH 45431 USA Texas A&M Univ Dept Mech Engn College Stn TX 77843 USA USAF Res Lab Control Design & Anal Branch Wright Patterson AFB OH 45433 USA USAF Inst Technol Dept Elect Engn Wright Patterson AFB OH 45433 USA 

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

年 卷 期：2012年第40卷第6期

页      面：487-491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：Approximate dynamic programming Linear programming State aggregation 

摘      要：A common approximate dynamic programming method entails state partitioning and the use of linear programming, i.e., the state-space is partitioned and the optimal value function is approximated by a constant over each partition. By minimizing a positive cost function defined on the partitions, one can construct an upper bound for the optimal value function. We show that this approximate value function is independent of the positive cost function and that it is the least upper bound, given the partitions. (C) 2012 Elsevier B.V. All rights reserved.