Results 81 to 90 of about 1,224,894 (351)

Using Functional Programming to recognize Named Structure in an Optimization Problem: Application to Pooling [PDF]

, 2016
Branch-and-cut optimization solvers typically apply generic algorithms, e.g., cutting planes or primal heuristics, to expedite performance for many mathematical optimization problems.
Ceccon, F, Kouyialis, G, Misener, R
core   +1 more source

Modelling and Optimizing the Process of Learning Mathematics [PDF]

, 2012
This paper introduces a computer-based training program for enhancing numerical cognition aimed at children with developmental dyscalculia. Through modelling cognitive processes and controlling the level of their stimulation, the system optimizes the learning process.
Käser, Tanja, Busetto, Alberto Giovanni, Baschera, Gian-Marco, Kohn, Juliane, Kucian, Karin, Aster, Michael, Gross, Markus   +6 more
openaire   +4 more sources

Predicting Feynman periods in ϕ 4-theory

Journal of High Energy Physics
We present efficient data-driven approaches to predict the value of subdivergence-free Feynman integrals (Feynman periods) in ϕ 4-theory from properties of the underlying Feynman graphs, based on a statistical examination of almost 2 million graphs.
Paul-Hermann Balduf, Kimia Shaban
doaj   +1 more source

Electrospinning Technology, Machine Learning, and Control Approaches: A Review

Advanced Engineering Materials, EarlyView.
Electrospinning produces micro‐ and nanoscale fibers, holding great promise in biomedical engineering. Industrial adoption faces challenges in controlling fiber properties, reproducibility, and scalability. This review explores electrospinning techniques, modeling, and machine learning for process optimization.
Arya Shabani, Gorkem Anil Al, Nael Berri, Bernardo Castro‐Dominguez, Hannah S. Leese, Uriel Martinez‐Hernandez   +5 more
wiley   +1 more source

A New Model for Reassignment of Tasks to Available Employees in Iraq’s Firms

International Journal of Mathematics and Mathematical Sciences, 2020
Generalized assignment problem (GAP) is a well-known problem in the combinatorial optimization. This problem is a specific form of assignment problem (AP) when the employees can carry out more than one task simultaneously or each work can be assigned to ...
Dhurgam Kalel Ibrahim Alsaad, Reza Ghanbari, Ali Akbar Sohrabi, Khatere Ghorbani Moghadam   +3 more
doaj   +1 more source

New sharp necessary optimality conditions for mathematical programs with equilibrium constraints [PDF]

arXiv, 2019
In this paper, we study the mathematical program with equilibrium constraints (MPEC) formulated as a mathematical program with a parametric generalized equation involving the regular normal cone. We derive a new necessary optimality condition which is sharper than the usual M-stationary condition and is applicable even when no constraint qualifications
arxiv  

A Case‐Based Reasoning Approach to Model Manufacturing Constraints for Impact Extrusion

Advanced Engineering Materials, EarlyView.
A hybrid modeling approach is presented that combines constraint‐based process modeling and case‐based reasoning. The model formalizes manufacturing constraints and integrates simulation data to model complex manufacturing processes. The approach supports manufacturability analysis during product design through an adaptive modeling environment.
Kevin Herrmann, Eduard Ortlieb, Hendrik Wester, Paul Christoph Gembarski, Bernd‐Arno Behrens, Roland Lachmayer   +5 more
wiley   +1 more source

Approximation of an Optimal BV -Control Problem in the Coefficient for the p(x)-Laplace Equation

Journal of Optimization, Differential Equations and Their Applications
We study a Dirichlet optimal control problem for a quasilinear monotone elliptic equation with the so-called weighted p(x)-Laplace operator. The coefficient of the p(x)-Laplacian, the weight u, we take as a control in BV (Ω) ∩ L∞(Ω).
Ismail Aydin, Peter Kogut
doaj   +1 more source

Numerical Optimization of Switching Ripples in the Double Dual Boost Converter through the Evolutionary Algorithm L-SHADE

Mathematics, 2020
Power-electronics based converters are essential circuits in renewable energy applications such as electricity generated with photovoltaic panels. The research on the field is getting increasing attention due to climate change problems and their possible
Alma Rodríguez, Avelina Alejo-Reyes, Erik Cuevas, Héctor R. Robles-Campos, Julio C. Rosas-Caro   +4 more
doaj   +1 more source

Mathematical Optimizations for Deep Learning

, 2018
Deep neural networks are often computationally expensive, during both the training stage and inference stage. Training is always expensive, because back-propagation requires high-precision floating-point multiplication and addition. However, various mathematical optimizations may be employed to reduce the computational cost of inference.
Çetin Kaya Koç, Çetin Kaya Koç, Sam Green, Craig M. Vineyard   +3 more
openaire   +4 more sources