PRAXIS
Scalar Function Optimization


PRAXIS, a MATLAB library which minimizes a scalar function of a vector argument, without needing derivative information, by Richard Brent.

PRAXIS seeks an M-dimensional point X which minimizes a given scalar function F(X). The code is a refinement of Powell's method of conjugate search directions. The user does not need to supply the partial derivatives of the function F(X). In fact, the function F(X) need not be smoothly differentiable.

Licensing:

The computer code and data files described and made available on this web page are distributed under the GNU LGPL license.

Languages:

PRAXIS is available in a C version and a C++ version and a FORTRAN90 version and a MATLAB version and a Python version.

Related Data and Programs:

BRENT, a MATLAB library which contains Richard Brent's routines for finding the zero, local minimizer, or global minimizer of a scalar function of a scalar argument, without the use of derivative information.

COMPASS_SEARCH, a MATLAB library which seeks the minimizer of a scalar function of several variables using compass search, a direct search algorithm that does not use derivatives.

praxis_test

TEST_OPT, a MATLAB library which defines test problems requiring the minimization of a scalar function of several variables.

TEST_OPT_CON, a MATLAB library which defines test problems for the minimization of a scalar function of several variables, with the search constrained to lie within a specified hyper-rectangle.

TEST_OPTIMIZATION, a MATLAB library which defines test problems for the minimization of a scalar function of several variables, as described by Molga and Smutnicki.

Author:

Original FORTRAN77 version by Richard Brent. MATLAB translation by John Burkardt.

Reference:

Source Code:


Last revised on 03 March 2019.