%
% Examples From the book: 
% 
% Practical Genetic Algorithms 
% by Haupt & Haupt.
%
% Epage: 44
%   
% Written by:
% -- 
% John L. Weatherwax                2006-08-28
% 
% email: wax@alum.mit.edu
% 
% Please send comments and especially bug reports to the
% above email address.
% 
%-----

close all; clc; clear all; 

% pick a function to study: 
% 
funnum = 7; % this function has a bounded domain 
funnum = 10; % this function has an unbounded domain 
%plot_test_functions % display this function 

wfn = @(x) fn_wrap(x,funnum);

addpath('../SHIP');

% The Nelder Mead method: 
% 
fprintf('first nelder mead solution\n');
x0_1 = [ 2, 3.; 2, 7.525; 8.5, 7.7 ]'; % start with a very large amoeba that does not surround the solution
nm_1 = nelder( x0_1, wfn, 0.00001 );
nm_1 = mean( nm_1', 1 )
wfn( nm_1 ) 

fprintf('second nelder mead solution\n');
x0_2 = [ 1, 1.; -1, 1; 0, -2 ]'; % start with a smaller amoeba surrounding the global optimum
nm_2 = nelder( x0_2, wfn, 0.00001 );
nm_2 = mean( nm_2', 1 )
wfn( nm_2 ) 

% The BFGS method: 
% 
fprintf('The BFGS solution\n');
bfgs_1 = bfgswopt( -[5;5], wfn, 0.00001 )
wfn( bfgs_1 ) 

% The steepest decent algorithm: 
%
fprintf('The SD solution\n');
sd_1 = steep( -[5;5], wfn, 0.00001 )
wfn( sd_1 )