Subgradients of optimal-value functions in dynamic programming: The case of convex systems without optimal paths

被引:18
作者
Seeger, A
机构
关键词
dynamic programming; discrete optimal control; sensitivity analysis; approximate subdifferential;
D O I
10.1287/moor.21.3.555
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
We study the first-order behaviour of the optimal-value function associated to a convex dynamic programming problem. The optimization process takes place in a certain environment characterized by some perturbation parameters affecting the transition costs and/or the evolution law of the dynamic system. An important aspect of this work is that we do not assume the existence of optimal paths to the unperturbed problem.
引用
收藏
页码:555 / 575
页数:21
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