sgalab_demo_mo_moga.m

多目标遗传算法程序 to run Demo files, is to run SGALAB_demo_*.m what s new: 1) Multiple-Objective GAs

% /*M-FILE SCRIPT SGALAB_demo_MO_MOGA MMM SGALAB */ %
% /*==================================================================================================
%  Simple Genetic Algorithm Laboratory Toolbox for Matlab 7.x
%
%  Copyright 2006 The SxLAB Family - Yi Chen - [e-mail]
% ====================================================================================================
%File description:
%
%Appendix comments:
%
%Usage:
%  We can run SGALAB by key-in "SGALAB_demo_MO_MOGA" in Matlab command
%  window
%===================================================================================================
%  See Also:         SGALAB_demo_math
%                    SGALAB_demo_MO_VEGA
%                    SGALAB_demo_MO_NPGA
%                    SGALAB_demo_MO_NSGA
%                    SGALAB_demo_MO_NSGAII
%                    SGALAB_demo_MO_VEGA
%                    SGALAB_demo_TSP_13cities
%
%===================================================================================================
%
%===================================================================================================
%Revision -
%Date        Name    Description of Change email                 Location
%27-Jun-2003 Chen Yi Initial version       [e-mail]  Chongqing
%14-Jan-2005 Chen Yi update 1003           [e-mail]  Shanghai
%HISTORY$
%==================================================================================================*/

% SGALAB_demo_MO_MOGA Begin

%% set screen
% fresh
clear ;
close ('all');
warning off
% to delete old output_*.txt
!del OUTPUT_*.txt
% set working path
%cd SGALAB_Funcs
%      SGA_set_working_paths

%% begin to count time during calculating
home ;
tic % timer start >>

% data preparation

%% open data files

%%%input data files
fid1  = fopen('INPUT_min_confines.txt' , 'r' );
fid2  = fopen('INPUT_max_confines.txt' , 'r' );
fid3  = fopen('INPUT_probability_crossover.txt' , 'r' );
fid4  = fopen('INPUT_probability_mutation.txt' , 'r' );
fid5  = fopen('INPUT_population.txt' , 'r' );
fid6  = fopen('INPUT_steps.txt' , 'r' );
fid7  = fopen('INPUT_max_generation.txt' , 'r' );
fid8  = fopen('INPUT_convergence_method.txt' , 'r' );
fid9  = fopen('INPUT_max_no_change_probability_crossover_generation.txt','r');
fid10 = fopen('INPUT_deta_fitness_max.txt','r');
fid11 = fopen('INPUT_max_probability_crossover.txt','r');
fid12 = fopen('INPUT_probability_crossover_step.txt','r');
fid13 = fopen('INPUT_max_no_change_fitness_generation.txt','r');

%output data files
fid14 = fopen('OUTPUT_maxfitness.txt','w+');
fid15 = fopen('OUTPUT_minfitness.txt','w+');
fid16 = fopen('OUTPUT_meanfitness.txt','w+');
fid17 = fopen('OUTPUT_best_result_space.txt','w+');
fid18 = fopen('OUTPUT_best_coding_space.txt','w+');
fid19 = fopen('OUTPUT_now_generation.txt','w+');
fid20 = fopen('OUTPUT_now_probability_crossover.txt','w+');

% begin to load data from file

%% read data from these files
disp('/*==================================================================================================*/')
disp('/*  Simple Genetic Algorithm Laboratory Toolbox (SGALAB) 1.0.0.3 for Matlab 7.x */ ')
disp('');
disp('    02-Aug-2005 Chen Yi update 1003     [e-mail]  Shanghai ')
disp('/*==================================================================================================*/')
disp('>>>>')
disp(' Begin to evaluate...Waiting please ...')


min_confines = fscanf( fid1 , '%g' ); min_confines = min_confines' ;

max_confines = fscanf( fid2 , '%g' ); max_confines = max_confines';

probability_crossover = fscanf( fid3 , '%g' ); probability_mutation = fscanf(fid4,'%g');

population = fscanf( fid5 , '%g' );

decimal_step = fscanf( fid6 , '%g' );

max_generation = fscanf( fid7 , '%g' );

convergence_method = fscanf( fid8 , '%g' );

max_no_change_probability_crossover_generation = fscanf( fid9 , '%g' );

deta_fitness_max = fscanf( fid10 , '%g' );

max_probability_crossover = fscanf( fid11,'%g' );

probability_crossover_step = fscanf(fid12,'%g');

max_no_change_fitness_generation = fscanf(fid13,'%g');

decimal_step = decimal_step' ;

now_probability_crossover = probability_crossover;
%

disp(' >>>>')
disp('End Evaluating, List of results :')

% Step into SGALAB()
options = { 'Binary',
    'Roulettewheel',
    'singlepoint',
    'singlepoint',
    '0',
    'MOGA'};

% Output

[ maxfitness ,...
    minfitness ,...
    meanfitness ,...
    now_generation , ...
    now_probability_crossover,...
    best_decimal_space ,...
    best_coding_space ,...
    error_status ]= SGA_entry_MO_Pareto_MOGA...
    ( options,...
    min_confines ,...
    max_confines ,...
    probability_crossover ,...
    probability_mutation ,...
    population ,...
    decimal_step , ...
    max_generation ,...
    convergence_method ,...
    max_no_change_probability_crossover_generation ,...
    deta_fitness_max ,...
    max_probability_crossover ,...
    max_no_change_fitness_generation ,...
    probability_crossover_step  );

if ( error_status ~= 0 )  return ;  end

%  [ maxfitness , minfitness , meanfitness , best_decimal_space , now_generation , now_probability_crossover , best_binary_space ] = SGALAB...
%  ( min_confines , max_confines , probability_crossover , probability_mutation , population , decimal_step , max_generation , convergence_method , max_no_change_probability_crossover_generation , deta_fitness_max , deta_fitness_max_min , max_probability_crossover , max_no_change_fitness_generation , probability_crossover_step );


%  maxfitness = max( fitness_value )
%  best_decimal_space = decimal_space( max_fitness_temp_position( population ) )

%write data to output files
% fprintf( fid8 , '\n the max value of fitness function:\n' );
fprintf( fid14 , '%f\n' , maxfitness);

%fprintf( fid9, '\n the min value of fitness function:\n');
fprintf( fid15 , '%f\n' ,minfitness);

%fprintf(fid10,'\n the mean value of fitness function:\n');
fprintf(fid16,'%f\n',meanfitness);

%fprintf( fid11,'\nthe best decimal space(x1 x2 x3...):\n');
fprintf( fid17,'%f\n',best_decimal_space );

fprintf( fid18 , '%f\n' , best_coding_space );

%fprintf( fid12, '\nthe generation number when end GAs:\n' );

fprintf( fid19, '%f\n' , now_generation );

fprintf( fid20, '%f\n' , now_probability_crossover );

%close files
status = fclose( 'all' );


disp(' More detail result in text files with " Output_*.txt " ' )
disp('----------------------------------------------------------------------------------------')
result_files = list_current_dir_files ('OUTPUT_*.txt')

disp('----------------------------------------------------------------------------------------')

% timer end
toc

% SGALAB_demo_MO_MOGA End