English
Related papers

Related papers: Automatic Ply Partitioning for Laminar Composite P…

200 papers

The Set Partitioning Problem is a combinatorial optimization problem with wide-ranging applicability, used to model various real-world tasks such as facility location and crew scheduling. However, real-world applications often require…

Optimization and Control · Mathematics 2025-03-24 Yasuyuki Ihara

Considering that the physical design of printed circuit board (PCB) follows the principle of modularized design, this paper proposes an automatic placement algorithm for functional modules. We first model the placement problem as a…

Other Computer Science · Computer Science 2025-02-21 Hangyuan Li , Zhaoyang Yang , Haotian Pang , Ning Xu , Yu Chen

We suggest an adaptive version of a partial linearization method for composite optimization problems. The goal function is the sum of a smooth function and a non necessary smooth convex separable function, whereas the feasible set is the…

Optimization and Control · Mathematics 2016-05-26 I. V. Konnov

This paper introduces a new method of partitioning the solution space of a multi-objective optimisation problem for parallel processing, called Efficient Projection Partitioning. This method projects solutions down into a single dimension,…

Optimization and Control · Mathematics 2017-11-23 William Pettersson , Melih Ozlen

This work explores a spatial printing method to fabricate continuous fiber-reinforced thermoplastic composites (CFRTPCs), which can achieve exceptional mechanical performance. For models giving complex 3D stress distribution under loads,…

Computational Geometry · Computer Science 2024-01-26 Guoxin Fang , Tianyu Zhang , Yuming Huang , Zhizhou Zhang , Kunal Masania , Charlie C. L. Wang

Stiffness degradation and progressive failure of composite laminates are complex processes involving evolution and multi-mode interactions among fiber fractures, intra-ply matrix cracks and inter-ply delaminations. This paper presents a…

Numerical Analysis · Mathematics 2023-11-06 Jiakun Liu , Stuart Leigh Phoenix

Additive manufacturing builds physical objects by accumulating layers upon layers of solidified material. This process is typically done with horizontal planar layers. However, fused filament printers have the capability to extrude material…

Graphics · Computer Science 2024-06-07 Emilio Ottonello , Pierre-Alexandre Hugron , Alberto Parmiggiani , Sylvain Lefebvre

Extensive compute and memory requirements limit the deployment of large language models (LLMs) on any hardware. Compression methods, such as pruning, can reduce model size, which in turn reduces resource requirements. State-of-the-art…

Machine Learning · Computer Science 2025-08-14 Bailey J. Eccles , Leon Wong , Blesson Varghese

The advancement of micro/nanofabrication techniques with high throughput, efficiency, and flexibility is critical for fields like integrated photonics, biosensing, and medical diagnostics. This study presents Partition Laser Assembling…

This paper is about partitioning in parallel and distributed simulation. That means decomposing the simulation model into a numberof components and to properly allocate them on the execution units. An adaptive solution based on…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-07 Gabriele D'Angelo

This paper presents a new concept to place continuous curved fibres for CFRP composites, which can be fulfilled by potential additive or hybrid manufacturing technology. Based on the loading condition, principal stress trajectories are…

Applied Physics · Physics 2018-02-15 Haoqi Zhang , Dongmin Yang , Yong Sheng

Large Language Models (LLMs) achieve strong performance across diverse tasks but face deployment challenges due to their massive size. Structured pruning offers acceleration benefits but leads to significant performance degradation. Recent…

Machine Learning · Computer Science 2026-02-03 Meng Li , Peisong Wang , Yuantian Shao , Qinghao Hu , Hongjian Fang , Yifan Zhang , Zhihui Wei , Jian Cheng

Reconfigurable multi-robot cells offer a promising approach to meet fluctuating assembly demands. However, the recurrent planning of their configurations introduces new challenges, particularly in generating optimized, coordinated…

Robotics · Computer Science 2026-05-29 Loris Schneider , Marc Ungen , Elias Huber , Jan-Felix Klein

Paper cutting is a simple process of slicing large rolls of paper, jumbo-reels, into various sub-rolls with variable widths based on demands risen by customers. Since the variability is high due to collected various orders into a pool, the…

Other Computer Science · Computer Science 2013-04-09 Mehmet E. Aydin , Osman Taylan

Seeking tighter relaxations of combinatorial optimization problems, semidefinite programming is a generalization of linear programming that offers better bounds and is still polynomially solvable. Yet, in practice, a semidefinite program is…

Optimization and Control · Mathematics 2023-11-17 Daniel Porumbel

Cutting-plane methods are well-studied localization(and optimization) algorithms. We show that they provide a natural framework to perform machinelearning ---and not just to solve optimization problems posed by machinelearning--- in…

Machine Learning · Computer Science 2015-08-13 Liva Ralaivola , Ugo Louche

The automated assembly of complex products requires a system that can automatically plan a physically feasible sequence of actions for assembling many parts together. In this paper, we present ASAP, a physics-based planning approach for…

Several recently proposed semi--automatic and fully--automatic coarse--graining schemes for polymer simulations are discussed. All these techniques derive effective potentials for multi--atom units or super--atoms from atomistic…

Soft Condensed Matter · Physics 2007-05-23 Roland Faller

We study the fabric spreading and cutting problem in apparel factories. For the sake of saving the material costs, the cutting requirement should be met exactly without producing additional garment components. For reducing the production…

Artificial Intelligence · Computer Science 2019-03-19 Xiuqin Shang , Dayong Shen , Fei-Yue Wang , Timo R. Nyberg

Current algorithms for large-scale industrial optimization problems typically face a trade-off: they either require exponential time to reach optimal solutions, or employ problem-specific heuristics. To overcome these limitations, we…

Quantum Physics · Physics 2025-10-16 Matteo Vandelli , Francesco Ferrari , Daniele Dragoni