Strong stationarity for a highly nonsmooth optimization problem with control constraints

IF 0.9 4区 数学 Q1 MATHEMATICS Mathematical Control and Related Fields Pub Date : 2022-01-01 DOI:10.3934/mcrf.2022047
Livia M. Betz
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引用次数: 4

Abstract

This paper deals with a control constrained optimization problem governed by a nonsmooth elliptic PDE in the presence of a non-differentiable objective. The nonsmooth non-linearity in the state equation is locally Lipschitz continuous and directionally differentiable, while one of the nonsmooth terms appearing in the objective is convex. Since these mappings are not necessarily Gâteaux-differentiable, the application of standard adjoint calculus is excluded. Based on their limited differentiability properties, we derive a strong stationary optimality system, i.e., an optimality system which is equivalent to the purely primal optimality condition saying that the directional derivative of the reduced objective in feasible directions is nonnegative.
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具有控制约束的高度非光滑优化问题的强平稳性
研究了一类具有不可微目标的非光滑椭圆偏微分方程控制约束优化问题。状态方程中的非光滑非线性是局部Lipschitz连续且方向可微的,而目标中出现的一个非光滑项是凸的。由于这些映射不一定是g teaux可微的,因此排除了标准伴随微积分的应用。基于它们的有限可微性,我们导出了一个强平稳最优性系统,即等价于简化目标在可行方向上的方向导数为非负的纯原始最优性条件的最优性系统。
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来源期刊
Mathematical Control and Related Fields
Mathematical Control and Related Fields MATHEMATICS, APPLIED-MATHEMATICS
CiteScore
2.50
自引率
8.30%
发文量
67
期刊介绍: MCRF aims to publish original research as well as expository papers on mathematical control theory and related fields. The goal is to provide a complete and reliable source of mathematical methods and results in this field. The journal will also accept papers from some related fields such as differential equations, functional analysis, probability theory and stochastic analysis, inverse problems, optimization, numerical computation, mathematical finance, information theory, game theory, system theory, etc., provided that they have some intrinsic connections with control theory.
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