Optimal Control Problem of Evolution Equation Governed by Hypergraph Laplacian

IF 1.7 2区 数学 Q2 MATHEMATICS, APPLIED
Takeshi Fukao, Masahiro Ikeda, Shun Uchida
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引用次数: 0

Abstract

In this paper, we consider an optimal control problem of an ordinary differential inclusion governed by the hypergraph Laplacian, which is defined as a subdifferential of a convex function and then is a set-valued operator. We can assure the existence of optimal control for a suitable cost function by using methods of a priori estimates established in the previous studies. However, due to the multivaluedness of the hypergraph Laplacian, it seems to be difficult to derive the necessary optimality condition for this problem. To cope with this difficulty, we introduce an approximation operator based on the approximation method of the hypergraph, so-called “clique expansion.” We first consider the optimality condition of the approximation problem with the clique expansion of the hypergraph Laplacian and next discuss the convergence to the original problem. In appendix, we state some basic properties of the clique expansion of the hypergraph Laplacian for future works.

超图拉普拉斯控制演化方程的最优控制问题
本文研究了一个由超图拉普拉斯算子控制的常微分包含的最优控制问题,该问题被定义为一个凸函数的子微分,然后是一个集值算子。利用前人研究中建立的先验估计方法,可以保证最优控制的存在性。然而,由于超图拉普拉斯算子的多值性,很难推导出该问题的最优性条件。为了解决这个困难,我们引入了一个基于超图近似方法的近似算子,即所谓的“团展开”。我们首先考虑了超图拉普拉斯算子的团展开逼近问题的最优性条件,然后讨论了逼近问题的收敛性。在附录中,我们给出了超图拉普拉斯的团展开的一些基本性质,以供以后的工作使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.30
自引率
5.60%
发文量
103
审稿时长
>12 weeks
期刊介绍: The Applied Mathematics and Optimization Journal covers a broad range of mathematical methods in particular those that bridge with optimization and have some connection with applications. Core topics include calculus of variations, partial differential equations, stochastic control, optimization of deterministic or stochastic systems in discrete or continuous time, homogenization, control theory, mean field games, dynamic games and optimal transport. Algorithmic, data analytic, machine learning and numerical methods which support the modeling and analysis of optimization problems are encouraged. Of great interest are papers which show some novel idea in either the theory or model which include some connection with potential applications in science and engineering.
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