Iterative Methods for OptimizationC.T. KelleyFrontiers in Applied Mathematics 18Matlab Code |
Iterative Methods for Optimization: Matlab Codes
- README : Curtent status.
- Compressed tar file with all matlab codes.
- Line Search Methods:
- steep.m : Steepest Descent
- gaussn.m : Damped Gauss-Newton
- bfgswopt.m : BFGS, low storage
- Polynomial line search routines: polyline.m , polymod.m
- Numerical Derivatives: diffhess.m :
Difference Hessian,
requires dirdero.m : directional derivative, as do several other codes
- Trust Region Codes:
- Bound Constrained Problems:
- gradproj.m : Gradient Projection Method
- projbfgs.m: Projected BFGS code
- Noisy Problems:
- imfil.m : Implicit Filtering
- nelder.m : Nelder-Mead
- simpgrad.m : Simplex Gradient, used in implicit filtering and Nelder-Mead codes
- hooke.m : Hooke-Jeeves code
- mds.m : Multidirectional Search code
- Fortran Codes for Noisy Problems
- The Paul Gilmore/Tony Choi FORTRAN code and users' guide for implicit filtering with bound constraints.
- Goerg Gablonsky's direct.tar.Z FORTRAN code for DIRECT with documentation
All computations reported in this book were done in MATLAB (version 5.2 on various SUN SPARCstations and on an Apple Macintosh Powerbook 2400).
One can obtain MATLAB from
The MathWorks, Inc.
3 Apple Hill Drive
Natick, MA 01760-2098 USA
Phone: 508-647-7000
Fax: 508-647-7001
E-mail: [email protected]
WWW: http://www.mathworks.com
Last modified: Jan 11, 1999