Shape optimization for interface identification in nonlocal models

IF 1.6 2区 数学 Q2 MATHEMATICS, APPLIED Computational Optimization and Applications Pub Date : 2024-05-07 DOI:10.1007/s10589-024-00575-7
Matthias Schuster, Christian Vollmann, Volker Schulz
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Abstract

Shape optimization methods have been proven useful for identifying interfaces in models governed by partial differential equations. Here we consider a class of shape optimization problems constrained by nonlocal equations which involve interface–dependent kernels. We derive a novel shape derivative associated to the nonlocal system model and solve the problem by established numerical techniques. The code for obtaining the results in this paper is published at (https://github.com/schustermatthias/nlshape).

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非局部模型界面识别的形状优化
事实证明,形状优化方法有助于识别偏微分方程模型中的界面。在此,我们考虑一类受非局部方程约束的形状优化问题,其中涉及与界面相关的核。我们推导出一种与非局部系统模型相关的新型形状导数,并通过成熟的数值技术解决该问题。获得本文结果的代码发布于 (https://github.com/schustermatthias/nlshape)。
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来源期刊
CiteScore
3.70
自引率
9.10%
发文量
91
审稿时长
10 months
期刊介绍: Computational Optimization and Applications is a peer reviewed journal that is committed to timely publication of research and tutorial papers on the analysis and development of computational algorithms and modeling technology for optimization. Algorithms either for general classes of optimization problems or for more specific applied problems are of interest. Stochastic algorithms as well as deterministic algorithms will be considered. Papers that can provide both theoretical analysis, along with carefully designed computational experiments, are particularly welcome. Topics of interest include, but are not limited to the following: Large Scale Optimization, Unconstrained Optimization, Linear Programming, Quadratic Programming Complementarity Problems, and Variational Inequalities, Constrained Optimization, Nondifferentiable Optimization, Integer Programming, Combinatorial Optimization, Stochastic Optimization, Multiobjective Optimization, Network Optimization, Complexity Theory, Approximations and Error Analysis, Parametric Programming and Sensitivity Analysis, Parallel Computing, Distributed Computing, and Vector Processing, Software, Benchmarks, Numerical Experimentation and Comparisons, Modelling Languages and Systems for Optimization, Automatic Differentiation, Applications in Engineering, Finance, Optimal Control, Optimal Design, Operations Research, Transportation, Economics, Communications, Manufacturing, and Management Science.
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