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Derivative-free - or zeroth-order - optimization (DFO) has gained recent attention for its ability to solve problems in a variety of application areas, including machine learning, particularly involving objectives which are stochastic…

Optimization and Control · Mathematics 2020-08-04 Coralia Cartis , Tyler Ferguson , Lindon Roberts

In industry, shape optimization problems are of utter importance when designing structures such as aircraft, automobiles and turbines. For many of these applications, the structure changes over time, with a prescribed or non-prescribed…

Optimization and Control · Mathematics 2020-01-29 Jørgen S. Dokken , Sebastian K. Mitusch , Simon W. Funke

We consider the problem of optimal location of a Dirichlet region in a $d$-dimensional domain $\Omega$ subjected to a given right-hand side $f$ in order to minimize some given functional of the configuration. While in the literature the…

Optimization and Control · Mathematics 2013-04-17 Giuseppe Buttazzo , Al-hassem Nayam

We present an extension of an algorithm for the classical scalar $p$-Laplace Dirichlet problem to the vector-valued $p$-Laplacian with mixed boundary conditions in order to solve problems occurring in shape optimization using a $p$-harmonic…

Optimization and Control · Mathematics 2022-08-16 Henrik Wyschka , Martin Siebenborn

This article presents an identification methodology to capture general relationships, with application to piecewise nonlinear approximations of model predictive control for constrained (non)linear systems. The mathematical formulation…

Optimization and Control · Mathematics 2017-01-06 Van-Vuong Trinh , Mazen Alamir , Patrick Bonnay

We model a microchannel cooling system and consider the optimization of its shape by means of shape calculus. A three-dimensional model covering all relevant physical effects and three reduced models are introduced. The latter are derived…

Optimization and Control · Mathematics 2025-10-14 Sebastian Blauth , Christian Leithäuser , René Pinnau

We introduce the Optimizing a Discrete Loss (ODIL) framework for the numerical solution of Partial Differential Equations (PDE) using machine learning tools. The framework formulates numerical methods as a minimization of discrete residuals…

Numerical Analysis · Mathematics 2024-01-23 Petr Karnakov , Sergey Litvinov , Petros Koumoutsakos

Most inverse optimization models impute unspecified parameters of an objective function to make an observed solution optimal for a given optimization problem with a fixed feasible set. We propose two approaches to impute unspecified…

Optimization and Control · Mathematics 2019-07-19 Timothy C. Y. Chan , Neal Kaw

This paper implements topology optimization on two-dimensional manifolds. In this paper, the material interpolation is implemented on a material parameter in the partial differential equation used to describe a physical field, when this…

Computational Physics · Physics 2020-04-22 Yongbo Deng , Zhenyu Liu , Jan G. Korvink

This article proposes a new discrete framework for approximating solutions to shape optimization problems under convexity constraints. The numerical method, based on the support function or the gauge function, is guaranteed to generate…

Optimization and Control · Mathematics 2022-03-15 Beniamin Bogosel

We propose a method that morphs high-orger meshes such that their boundaries and interfaces coincide/align with implicitly defined geometries. Our focus is particularly on the case when the target surface is prescribed as the zero…

Computational Geometry · Computer Science 2023-02-17 Jorge-Luis Barrera , Tzanio Kolev , Ketan Mittal , Vladimir Tomov

This work develops an algorithm for PDE-constrained shape optimization based on Lipschitz transformations. Building on previous work in this field, the $p$-Laplace operator is utilized to approximate a descent method for Lipschitz shapes.…

Optimization and Control · Mathematics 2023-04-24 Peter Marvin Müller , Jose Pinzon , Thomas Rung , Martin Siebenborn

Symmetry detection and morphological classification of anatomical structures play pivotal roles in medical image analysis. The application of kinematic surface fitting, a method for characterizing shapes through parametric stationary…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Wilhelm Wimmer , Hervé Delingette

We discuss computational and qualitative aspects of the fractional Plateau and the prescribed fractional mean curvature problems on bounded domains subject to exterior data being a subgraph. We recast these problems in terms of energy…

Numerical Analysis · Mathematics 2021-05-14 Juan Pablo Borthagaray , Wenbo Li , Ricardo H. Nochetto

We propose a new decomposition framework for continuous nonlinear constrained two-stage optimization, where both first- and second-stage problems can be nonconvex. A smoothing technique based on an interior-point formulation renders the…

Optimization and Control · Mathematics 2026-03-02 Yuchen Lou , Xinyi Luo , Andreas Wächter , Ermin Wei

In component shape optimization, the component properties are often evaluated by computationally expensive simulations. Such optimization becomes unfeasible when it is focused on a global search requiring thousands of simulations to be…

Computational Engineering, Finance, and Science · Computer Science 2025-12-08 Lucie Kubíčková , Onřej Gebouský , Jan Haidl , Martin Isoz

A numerical method for coupled 3D-1D problems with discontinuous solutions at the interfaces is derived and discussed. This extends a previous work on the subject where only continuous solutions were considered. Thanks to properly defined…

Numerical Analysis · Mathematics 2022-03-04 Stefano Berrone , Denise Grappein , Stefano Scialò

In this paper we present a framework for automated shape differentiation in the finite element software NGSolve. Our approach combines the mathematical Lagrangian approach for differentiating PDE constrained shape functions with the…

Optimization and Control · Mathematics 2026-04-01 Peter Gangl , Kevin Sturm , Michael Neunteufel , Joachim Schöberl

We develop a density based topology optimization method for linear elasticity based on the cut finite element method. More precisely, the design domain is discretized using cut finite elements which allow complicated geometry to be…

Numerical Analysis · Mathematics 2019-03-19 Erik Burman , Daniel Elfverson , Peter Hansbo , Mats G. Larson , Karl Larsson

We propose and analyze several inexact regularized Newton-type methods for finding a global saddle point of convex-concave unconstrained min-max optimization problems. Compared to first-order methods, our understanding of second-order…

Optimization and Control · Mathematics 2026-05-27 Tianyi Lin , Panayotis Mertikopoulos , Michael I. Jordan