LOCAL_MIN_RC
Reverse Communication Function for Local Minimum, by Richard Brent


LOCAL_MIN_RC is a Python library which seeks a local minimum of a scalar function of a scalar variable, without requiring derivatives, or assuming the function is differentiable, using reverse communication (RC), by Richard Brent.

Licensing:

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

Languages:

LOCAL_MIN_RC 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:

BACKTRACK_BINARY_RC, a Python library which carries out a backtrack search for a set of binary decisions, using reverse communication (RC).

BISECTION_RC, a Python library which demonstrates the simple bisection method for solving a scalar nonlinear equation in a change of sign interval, using reverse communication (RC).

CG_RC, a Python library which implements the conjugate gradient (CG) method for solving a positive definite sparse linear system A*x=b, using reverse communication (RC).

ROOT_RC, a Python library which seeks a solution of a scalar nonlinear equation f(x) = 0, or a system of nonlinear equations, using reverse communication (RC), by Gaston Gonnet.

ROOTS_RC, a Python library which seeks a solution of a system of nonlinear equations f(x) = 0, using reverse communication (RC), by Gaston Gonnet.

SORT_RC, a Python library which can sort a list of any kind of objects, using reverse communication (RC).

ZERO_RC, a Python library which seeks a solution of a scalar nonlinear equation f(x) = 0, using reverse communication (RC), by Richard Brent.

Author:

Original FORTRAN77 version by Richard Brent; Python version by John Burkardt.

Reference:

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

Source Code:

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


Last revised on 30 November 2016.