ASA047
Nelder-Mead Minimization Algorithm

ASA047 is a Python library which seeks to minimize a scalar function of several variables using the Nelder-Mead algorithm, by R ONeill.

ASA047 is Applied Statistics Algorithm 47. Source code for many Applied Statistics Algorithms is available through STATLIB.

Licensing:

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

Languages:

ASA047 is available in a C version and a C++ version and a FORTRAN90 version and a MATLAB version and a Python version.

Author:

Original FORTRAN77 version by R ONeill; Python version by John Burkardt.

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

TOMS178, a Python library which optimizes a scalar functional of multiple variables using the Hooke-Jeeves method, by Arthur Kaupe. This is a version of ACM TOMS algorithm 178.

Reference:

1. John Nelder, Roger Mead,
   A simplex method for function minimization,
   Computer Journal,
   Volume 7, 1965, pages 308-313.
2. R ONeill,
   Algorithm AS 47: Function Minimization Using a Simplex Procedure,
   Applied Statistics,
   Volume 20, Number 3, 1971, pages 338-345.

Source Code:

• asa047.py minimizes a function using the Nelder-Mead algorithm.

Examples and Tests:

• asa047.sh, runs all the tests.
• asa047.txt, the output file.

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