Results 271 to 280 of about 125,451 (299)
Some of the next articles are maybe not open access.
Finding Optimal Algorithmic Parameters Using Derivative‐Free Optimization
SIAM Journal on Optimization, 2006The objectives of this paper are twofold. We devise a general framework for identifying locally optimal algorithmic parameters. Algorithmic parameters are treated as decision variables in a problem for which no derivative knowledge or existence is assumed.
Charles Audet, Dominique Orban
openaire +1 more source
A derivative-free algorithm for spherically constrained optimization
Journal of Global Optimization, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Min Xi +3 more
openaire +2 more sources
Penalty Fuzzy Function for Derivative-Free Optimization
2011Penalty and Barrier methods are normally used to solve Nonlinear Optimization Constrained Problems. The problems appear in areas such as engineering and are often characterized by the fact that involved functions (objective and constraints) are non-smooth and/or their derivatives are not know.
João Matias +5 more
openaire +2 more sources
A Discussion on Variational Analysis in Derivative-Free Optimization
Set-Valued and Variational Analysis, 2020Derivative-Free Optimization (DFO) is the mathematical study of algorithms for continuous optimization that do not use first-order information. Thus, by definition, DFO studies algorithms that do not use derivatives, gradients, directional derivatives, subgradients, normal cones, tangent cones, etc.
openaire +1 more source
Optimizing autocatalysis with uncertainty by derivative‐free estimators
Optimal Control Applications and Methods, 2020SummaryA derivative‐free estimator was introduced to alleviate the drawbacks of the conventional Kalman filter when performing nonlinear analyses under different circumstances. In this work, the scaled Unscented Kalman Filter, Divided Difference Kalman filter, and Cubature Kalman filter (CKF) were selected to investigate the effectiveness of these ...
Fakhrony S. Rohman +3 more
openaire +1 more source
Algorithm for forming derivative-free optimal methods
Numerical Algorithms, 2013The Newton method is the best known method for solving a nonlinear equation \(f(x)=0\) which is given as \[ x_{n+1}=x_n-\frac{f(x_n)}{f'(x_n)}, \qquad n=0,1,2,\dots, \qquad |f'(x_n)|\neq 0. \] A scheme for constructing optimal derivative free iterative methods is the main aim of the article. The derivative in Newton's method is approximated as follows \
Sanjay Kumar Khattri, Trond Steihaug
openaire +2 more sources
Derivative-free optimization of hearing aid parameters
2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013Loudness restoration approaches to hearing aid fitting prescribe gain and compression so as to restore the loudness perceived by a hearing-impaired listener to that perceived by a listener with normal-hearing. Restoring the loudness perception to normal is complicated by the spread of excitation at high stimulus levels that causes intense stimuli at ...
Shu-Hsien Chu +5 more
openaire +1 more source
Objective-derivative-free methods for constrained optimization
Mathematical Programming, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
LUCIDI, Stefano, M. Sciandrone, P. Seng
openaire +5 more sources
On the numerical performance of finite-difference-based methods for derivative-free optimization
Optimization Methods and Software, 2023Jorge Nocedal
exaly