The goal of this toolbox is to provide unconstrained optimization problems
in order to test optimization algorithms.
The More, Garbow and Hillstrom collection of test functions is widely used
in testing unconstrained optimization software. The code for these problems
is available in Fortran from the netlib software archives.
The port from Fortran to Matlab was done by two undergraduate students at
Livia Klein and Madhu Lamba, under the supervision of Chaya Gurwitz.
Benoit Hamelin did the port from Matlab to Scilab v4 with m2sci and
did some manual tuning of the result.
Michael Baudin did the port from Scilab v4 to Scilab v5.
I renamed the functions to avoid naming conflicts.
I formatted the help pages to generate automatically the xml from the
Provides 35 unconstrained optimization problems.
Provide the function value, the gradient, the function vector, the Jacobian.
Provide the Hessian matrix for 18 problems.
Provides the starting point for each problem.
Provides the optimum function value and the optimum point x for many problems.
Provide finite difference routines for the gradient, the Jacobian and the
Macro based functions : no compiler required.
All function values, gradients, Jacobians and Hessians are tested.
"Algorithm 566: FORTRAN Subroutines for Testing Unconstrained Optimization
Software", ACM Transactions on Mathematical Software (TOMS), Volume 7 , Issue
1, March 1981, Pages: 136 - 140, J. J. Moré, Burton S. Garbow, Kenneth E.
"HESFCN - A Fortran Package Of Hessian Subroutines For Testing Nonlinear
Software", Victoria Averbukh, Samuel Figueroa, And Tamar Schlick Courant
Institue Of Mathematical Sciences
Scilab v5 port and update: 2010, Michael Baudin
Scilab port: 2000-2004, Benoit Hamelin, Jean-Pierre Dussault
Matlab port: Chaya Gurwitz, Livia Klein, and Madhu Lamba
2000 - John Burkardt (optimum points for problem #20)
Fortran 77: Jorge More, Burton Garbow and Kenneth Hillstrom