local_min


local_min, a FORTRAN90 code which finds a local minimizer of a scalar function of a scalar variable, by Richard Brent.

The method does not require the use of derivatives, and does not assume that the function is differentiable.

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 is available in a C version and a C++ version and a FORTRAN90 version and a MATLAB version and an Octave version and a Python version and an R version.

Related Data and Programs:

local_min_test

asa047, a FORTRAN90 code which minimizes a scalar function of several variables using the Nelder-Mead algorithm.

compass_search, a FORTRAN90 code which seeks the minimizer of a scalar function of several variables using compass search, a direct search algorithm that does not use derivatives.

nms, a FORTRAN90 code which includes versions of Brent's minimizer and zero finder.

praxis, a FORTRAN90 code which minimizes a scalar function of several variables.

test_opt, a FORTRAN90 code which defines test problems requiring the minimization of a scalar function of several variables.

test_optimization, a FORTRAN90 code which defines test problems for the minimization of a scalar function of several variables, as described by Molga and Smutnicki.

toms178, a FORTRAN90 code which optimizes a scalar functional of multiple variables using the Hooke-Jeeves method.

Author:

Original FORTRAN77 version by Richard Brent; FORTRAN90 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:


Last revised on 11 June 2021.