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+++ b/inst/ga.m
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+## Copyright (C) 2008 Luca Favatella <slackydeb@gmail.com>
+##
+##
+## This program is free software; you can redistribute it and/or modify it
+## under the terms of the GNU General Public License as published by
+## the Free Software Foundation; either version 2, or (at your option)
+## any later version.
+##
+## This program  is distributed in the hope that it will be useful, but
+## WITHOUT ANY WARRANTY; without even the implied warranty of
+## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with this program; see the file COPYING.  If not, write to the Free
+## Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
+## 02110-1301, USA.
+
+## -*- texinfo -*-
+## @deftypefn{Function File} {@var{x} =} ga (@var{fitnessfcn}, @var{nvars})
+## @deftypefnx{Function File} {@var{x} =} ga (@var{fitnessfcn}, @var{nvars}, @var{options})
+## @deftypefnx{Function File} {@var{x} =} ga (@var{problem})
+## Find minimum of function using genetic algorithm.
+##
+## @strong{Inputs}
+## @table @var
+## @item fitnessfcn
+## The objective function to minimize. It accepts a vector @var{x} of size 1-by-@var{nvars}, and returns a scalar evaluated at @var{x}.
+## @item nvars
+## The number of variables of @var{fitnessfcn}.
+## @item options
+## The structure of the optimization parameters; can be created with using the @code{gaoptimset} function. If not specified, @code{ga} minimizes with the default optimization parameters.
+## @item problem
+## A structure containing the following fields: @var{fitnessfcn}, @var{nvars} and @var{options}.
+## @end table
+##
+## @strong{Outputs}
+## @table @var
+## @item x
+## The local unconstrained found minimum to the objective function.
+## @end table
+##
+## @seealso{gaoptimset}
+## @end deftypefn
+
+## Author: Luca Favatella <slackydeb@gmail.com>
+## Version: 3.1
+
+function x = ga (varargin)
+	if ((nargout > 1) || (length (varargin) <1) || (length (varargin) > 3))
+		print_usage ();
+	else
+		switch (length (varargin))
+			case (1)
+				problem = varargin{1};
+			case (2)
+				problem.fitnessfcn = varargin{1};
+				problem.nvars = varargin{2};
+				problem.options = gaoptimset;
+			case (3)
+				problem.fitnessfcn = varargin{1};
+				problem.nvars = varargin{2};
+				problem.options = varargin{3};
+		endswitch
+
+		x = __ga_problem__ (problem);
+	endif
+endfunction
+
+%!function retval = test_4_variabili (x)
+%! retval = 0;
+%! retval += 20 + (x(1) ** 2) + (x(2) ** 2) - 10 * (cos (2 * pi * x(1)) + cos (2 * pi * x(2)));
+%! retval += (x(3) ** 2) - (cos (2 * pi * x(3))) + 1;
+%! retval += x(4) ** 2;
+
+%!assert (ga (@test_4_variabili, 4, gaoptimset ('FitnessLimit', 0.001, 'PopInitRange', [-1; 1])), [0, 0, 0, 0], sqrt(0.001))
+
+%!function retval = test_rastriginsfcn_traslato (t)
+%! min = [1, 0];
+%! x = t - min;
+%! retval = 20 + (x(1) ** 2) + (x(2) ** 2) - 10 * (cos (2 * pi * x(1)) + cos (2 * pi * x(2)));
+
+%!assert (ga (@test_rastriginsfcn_traslato, 2, gaoptimset ('FitnessLimit', 0.001, 'PopInitRange', [-2; 2], 'PopulationSize', 100)), [1, 0], sqrt(0.001))
+
+%!function retval = test_rastriginsfcn (x)
+%! retval = 20 + (x(1) ** 2) + (x(2) ** 2) - 10 * (cos (2 * pi * x(1)) + cos (2 * pi * x(2)));
+
+%!assert (ga (@test_rastriginsfcn, 2), [0, 0], 1e-6)
+
+%!function retval = test_f_con_inf_minimi_locali (x)
+%! retval = (x ** 2) - (cos (2 * pi * x)) + 1;
+
+%!assert (ga (@test_f_con_inf_minimi_locali, 1, gaoptimset ('CrossoverFcn', @crossoversinglepoint, 'EliteCount', 1, 'FitnessLimit', 0.001, 'Generations', 25, 'PopInitRange', [-5; 5])), 0, sqrt(0.001)) 
+
+%!function retval = test_parabola (x)
+%! retval = x ** 2;
+
+%!assert (ga (@test_parabola, 1, gaoptimset ('CrossoverFcn', @crossoversinglepoint, 'EliteCount', 1, 'FitnessLimit', 0.001, 'Generations', 10, 'PopInitRange', [-1; 1])), 0, sqrt(0.001))