cg_plus

cg_plus, a FORTRAN77 code which seeks the multidimensional minimizer x of a scalar function f(x) using the conjugate gradient method, assuming that the gradient vector g(x) can be computed, by Guanghui Liu, Jorge Nocedal, Richard Waltz.

To set up the code to minimize a particular function you need to specify the following variables in the main program:

• n the number of variables
• x the initial input vector
• method the form of the conjugate gradient method used to solve the problem:
  1. Fletcher-Reeves;
  2. Polak-Ribiere;
  3. positive Polak-Ribiere (beta = max{beta,0});

Licensing:

This software is freely available for educational or commercial use, but we expect that all publications describing work using this software quote the Gilbert and Nocedal reference given below.

Languages:

cg_plus is available in a FORTRAN77 version.

Related Data and Programs:

cg_plus_test

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Reference:

1. https://users.iems.northwestern.edu/~nocedal/CG+.html
2. Jean Charles Gilbert, Jorge Nocedal,
   Global Convergence Properties of Conjugate Gradient Methods,
   SIAM Journal on Optimization,
   Volume 2, Number 1, 1992, pages 21-42.
3. Jorge More, David Thuente,
   Linesearch Algorithms with Guaranteed Sufficient Decrease,
   ACM Transactions on Mathematical Software,
   Volume 20, Number 3, September 1994, pages 286-307.

Source Code:

• cg_plus.f, the source code.
• cg_plus.sh, commands to compile the source code.