# PRAXIS Scalar Function Optimization

PRAXIS is 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.

### Languages:

PRAXIS is available in a C version and a C++ version and a FORTRAN77 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.

ENTRUST, a MATLAB program which solves problems in scalar optimization or nonlinear least squares.

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.

### Reference:

• Richard Brent,
Algorithms for Minimization without Derivatives,
Dover, 2002,
ISBN: 0-486-41998-3,
LC: QA402.5.B74.

### Examples and Tests:

You can go up one level to the MATLAB source codes.

Last revised on 31 July 2016.