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Evolutionary multiobjective optimization (EMO) has made significant strides over the past two decades. However, as problem scales and complexities increase, traditional EMO algorithms face substantial performance limitations due to…

Neural and Evolutionary Computing · Computer Science 2025-07-11 Zhenyu Liang , Hao Li , Naiwei Yu , Kebin Sun , Ran Cheng

We present an application of multi-mesh finite element methods as part of a methodology for optimizing settlement layouts. By formulating a multi-objective optimization problem, we demonstrate how a given number of buildings may be…

Computational Engineering, Finance, and Science · Computer Science 2023-01-31 Anders Logg , Christian Valdemar Lorenzen , Carl Lundholm

We present a topological framework for finding low-flop algorithms for evaluating element stiffness matrices associated with multilinear forms for finite element methods posed over straight-sided affine domains. This framework relies on…

Numerical Analysis · Mathematics 2012-05-15 Robert C. Kirby , Anders Logg , L. Ridgway Scott , Andy R. Terrel

Element-based topology optimization algorithms capable of generating smooth boundaries have drawn serious attention given the significance of accurate boundary information in engineering applications. The basic framework of a new…

Computational Engineering, Finance, and Science · Computer Science 2021-01-11 Yun-Fei Fu , Bernard Rolfe , Ngai Sum Louis Chiu , Yanan Wang , Xiaodong Huang , Kazem Ghabraie

Efficient exploitation of exascale architectures requires rethinking of the numerical algorithms used in many large-scale applications. These architectures favor algorithms that expose ultra fine-grain parallelism and maximize the ratio of…

We present a new high order finite element method for the discretization of partial differential equations on stationary smooth surfaces which are implicitly described as the zero level of a level set function. The discretization is based…

Numerical Analysis · Mathematics 2017-04-17 Jörg Grande , Christoph Lehrenfeld , Arnold Reusken

The finite element method (FEM) is a well-established numerical method for solving partial differential equations (PDEs). However, its mesh-based nature gives rise to substantial computational costs, especially for complex multiscale…

Computational Engineering, Finance, and Science · Computer Science 2025-06-24 Weihang Ouyang , Yeonjong Shin , Si-Wei Liu , Lu Lu

We propose a general algorithm for non-conforming adaptive mesh refinement (AMR) of unstructured meshes in high-order finite element codes. Our focus is on h-refinement with a fixed polynomial order. The algorithm handles triangular,…

Numerical Analysis · Computer Science 2019-05-13 Jakub Červený , Veselin Dobrev , Tzanio Kolev

A simple and efficient interface-fitted mesh generation algorithm is developed in this paper. This algorithm can produce a local anisotropic fitting mixed mesh which consists of both triangles and quadrilaterals near the interface. A new…

Numerical Analysis · Mathematics 2020-05-13 Jun Hu , Hua Wang

We present a Pseudo-Transient Topology Optimization (PeTTO) approach that can leverage graphics processing units (GPUs) to efficiently solve single-material and multi-material topology optimization problems. By integrating PeTTO with phase…

Numerical Analysis · Mathematics 2025-09-10 Mingyuan Yang , Qian Yu , Chao Yang

During design optimization, a smooth description of the geometry is important, especially for problems that are sensitive to the way interfaces are resolved, e.g., wave propagation or fluid-structure interaction. A levelset description of…

Computational Engineering, Finance, and Science · Computer Science 2021-12-28 Sanne J. van den Boom , Jian Zhang , Fred van Keulen , Alejandro M. Aragón

In [Heimann, Lehrenfeld, Preu{\ss}, SIAM J. Sci. Comp. 45(2), 2023, B139 - B165] new geometrically unfitted space-time Finite Element methods for partial differential equations posed on moving domains of higher-order accuracy in space and…

Numerical Analysis · Mathematics 2025-03-14 Fabian Heimann , Christoph Lehrenfeld

The optimization of submodular functions constitutes a viable way to perform clustering. Strong approximation guarantees and feasible optimization w.r.t. streaming data make this clustering approach favorable. Technically, submodular…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-01-22 Philipp-Jan Honysz , Sebastian Buschjäger , Katharina Morik

Energy system optimization models are increasing in scope and resolution, yielding large and challenging linear programs. For a long time, the standard way to address such problems has relied on shared-memory interior-point methods (IPM),…

Optimization and Control · Mathematics 2026-05-07 Janina Zittel , Annika Buchholz , Michael Bussieck , Frederik Fiand , Thorsten Koch , Lukas Mehl , Niels Lindner , Manuel Wetzel

We consider a linear symmetric and elliptic PDE and a linear goal functional. We design and analyze a goal-oriented adaptive finite element method, which steers the adaptive mesh-refinement as well as the approximate solution of the arising…

Numerical Analysis · Mathematics 2024-01-12 Roland Becker , Gregor Gantner , Michael Innerberger , Dirk Praetorius

Topology optimization (TO) has experienced a dramatic development over the last decades aided by the arising of metamaterials and additive manufacturing (AM) techniques, and it is intended to achieve the current and future challenges. In…

Sequential robot manipulation tasks require finding collision-free trajectories that satisfy geometric constraints across multiple object interactions in potentially high-dimensional configuration spaces. Solving these problems in real-time…

Robotics · Computer Science 2025-10-14 Lucas Chen , Shrutheesh Raman Iyer , Zachary Kingston

Batch planning is increasingly necessary to quickly produce diverse and quality motion plans for downstream learning applications, such as distillation and imitation learning. This paper presents Global Tensor Motion Planning (GTMP) -- a…

Robotics · Computer Science 2025-05-30 An T. Le , Kay Hansel , João Carvalho , Joe Watson , Julen Urain , Armin Biess , Georgia Chalvatzaki , Jan Peters

Recent hardware acceleration advances have enabled powerful specialized accelerators for finite element computations, spiking neural network inference, and sparse tensor operations. However, existing approaches face fundamental limitations:…

Hardware Architecture · Computer Science 2026-01-09 Chuanzhen Wang , Leo Zhang , Eric Liu

A new higher-order accurate method is proposed that combines the advantages of the classical $p$-version of the FEM on body-fitted meshes with embedded domain methods. A background mesh composed by higher-order Lagrange elements is used.…

Numerical Analysis · Computer Science 2016-04-04 Samir Omerović , Thomas-Peter Fries
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