Quasi- Newton Methods for Nonlinear Equations
Journal of the ACM (JACM)
Lattice Approximations to the Minima of Functions of Several Variables
Journal of the ACM (JACM)
A View of Unconstrained Minimization Algorithms that Do Not Require Derivatives
ACM Transactions on Mathematical Software (TOMS)
Algorithm 611: Subroutines for Unconstrained Minimization Using a Model/Trust-Region Approach
ACM Transactions on Mathematical Software (TOMS)
On the Benefits of Random Memorizing in Local Evolutionary Search
RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
Algorithms for nonlinear problems which use discrete approximations to derivatives
ACM '71 Proceedings of the 1971 26th annual conference
Assessment of True Worst Case Circuit Performance Under Interconnect Parameter Variations
ISQED '01 Proceedings of the 2nd International Symposium on Quality Electronic Design
A robust conjugate-gradient algorithm which minimizes L-functions
Automatica (Journal of IFAC)
Development of predictor models
Automatica (Journal of IFAC)
A nonlinear programming approach for optimizing two-stage lifting vehicle ascent to orbit
Automatica (Journal of IFAC)
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A modification of Davidon's method for the unconstrained minimization of a function of several variables is proposed in which the gradient vector is approximated by differences. The step sizes for the differencing are calculated from information available in the course of the minimization and are chosen to approximately balance off the effects of truncation error and cancellation error. Numerical results and comparisons with other methods are given.