Two Approaches to Stochastic Optimal Control Problems with a Final-Time Expectation Constraint

被引：10
|
作者：
Pfeiffer, Laurent [1 ]
机构：
[1] Karl Franzens Univ Graz, Inst Math & Sci Comp, Heinrichstr 36, A-8010 Graz, Austria
来源：
APPLIED MATHEMATICS AND OPTIMIZATION | 2018年 / 77卷 / 02期
基金：
奥地利科学基金会;
关键词：
Stochastic optimal control; Expectation and probability constraints; Dynamic programming; Lagrange relaxation;
D O I：
10.1007/s00245-016-9378-9
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this article, we study and compare two approaches to solving stochastic optimal control problems with an expectation constraint on the final state. The case of a probability constraint is included in this framework. The first approach is based on a dynamic programming principle and the second one uses Lagrange relaxation. In this article, we focus on discrete-time problems, but the two discussed approaches can be applied to discretized continuous-time problems.
引用
收藏
页码：377 / 404
页数：28
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