sga_pro_demo.m

遗传算法2的例子

%test sga_pro
clear;
home
tic
% open data files
fid1=fopen('min_confines.txt','r');
fid2=fopen('max_confines.txt','r');
fid3=fopen('probability_crossover.txt','r');
fid4=fopen('probability_mutation.txt','r');
fid5=fopen('population.txt','r');
fid6=fopen('decimal_step.txt','r');
fid7=fopen('max_generation.txt','r');
%
fid8=fopen('maxfitness.txt','w+');
fid9=fopen('minfitness.txt','w+');
fid10=fopen('meanfitness.txt','w+');
fid11=fopen('best_decimal_space.txt','w+');
fid12=fopen('best_binary_space.txt','w+');
%


%read data from these files
%disp(' input parameters:')
%disp('~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~')
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');
max_generation=fscanf(fid7,'%g');
decimal_step=fscanf(fid6,'%g');
decimal_step=decimal_step';

%
%disp('begin to work,Waiting please ...')
%disp('O.K')
%disp('works results ~~~~~~~~~~~~~~~~~~~~~~~')
[maxfitness,minfitness,meanfitness,best_decimal_space,best_binary_space]=SGA_pro(min_confines,max_confines,probability_crossover,probability_mutation,population,decimal_step,max_generation);
%maxfitness=max(fitness_value)
%best_decimal_space=decimal_space(max_fitness_temp_position(population))

fprintf(fid8,'%f\n',maxfitness);

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

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

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

fprintf(fid12,'%f\n',best_binary_space);

status=fclose('all');

disp('End sga_pro_demo ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~')
%clear;
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