A STOPPING RULE FOR FORECAST HORIZONS IN NONHOMOGENEOUS MARKOV DECISION-PROCESSES
成果类型：
Article
署名作者：
BEAN, JC; HOPP, WJ; DUENYAS, I
署名单位：
Northwestern University
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.40.6.1188
发表日期：
1992
页码：
1188-1199
关键词：
摘要：
We formulate a mixed integer program to determine whether a finite time horizon is a forecast horizon in a nonhomogeneous Markov decision process. We give a Bender's decomposition approach to solving this problem that evaluates the stopping rule, eliminates some suboptimal combinations of actions, and yields bounds on the maximum error that could result from the selection of a candidate action in the initial stage. The integer program arising from the decomposition has special properties that allow efficient solution. We illustrate the approach with numerical examples.