请哪位高手帮我看看遗传算法的程序吧

huohuo

怎么总是求不出最优解呢 如能指点一二 小弟不胜感激
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Main
clc
clear
global T0_7 T0_8 T0_11 T0_12
global K F DD
global theta
load 'T0_7.mat'
load 'T0_8.mat'
load 'T0_11.mat'
load 'T0_12.mat'
load 'K.mat'
load 'F.mat'
load 'DD.mat'
load 'theta.mat'
groupsize= 100;
var_num= 10;
var_length= 10;
var_min= 100;
var_max= 4000;
Pc= 0.85;
Pm= 0.001;
e= 1e-6;
Initial_group= Initial(groupsize,var_min,var_max,var_num,var_length);

mins= min(Initial_group(:,end));
r=1;
while mins>=e
    select_group= Select(Initial_group,var_num,var_length,groupsize);
    % 交叉
    t= 1;
    while t<= groupsize/2
        parent1_num= floor(rand*groupsize)+1;
        parent2_num= floor(rand*groupsize)+1;
        parent1= select_group(parent1_num,:);
        parent2= select_group(parent2_num,:);
        [child1,child2]= Cross(parent1,parent2,Pc,var_num,var_length,groupsize);
        cross_group(t,:)= child1;
        cross_group(t+groupsize/2,:)= child2;
        t=t+1;
    end
    % 变异
    t= 1;
    while t<= groupsize
        parent_num= floor(rand*groupsize)+1;
        parent= select_group(parent_num,:);
        child= Mutation(parent,Pm,var_num,var_length);
        mutation_group(t,:)= child;
        t=t+1;
    end
    Initial_group= mutation_group;
    r= r+1;
    mins= min(mutation_group(:,end));
end


function [Initial_group]= Initial(groupsize,var_min,var_max,var_num,var_length)
Initial_group= round(rand(groupsize,(var_num+1)*var_length+1));
for k= 1:var_num
Initial_group(:,var_num*var_length+k)= bi2de(Initial_group(:,(k-1)*var_length+1:k*var_length));
end
for k= 1:groupsize
Initial_group(k,(var_num+1)*var_length+1)= Fun(Initial_group(k,var_num*var_length+1:(var_num+1)*var_length));
end


function [select_group]= Select(parent_group,var_num,var_length,groupsize)
parent_group(:,(var_num+1)*var_length+1)= 1./parent_group(:,(var_num+1)*var_length+1);
total_fitness= sum(parent_group(:,(var_num+1)*var_length+1));
parent_group(:,(var_num+1)*var_length+1)= parent_group(:,(var_num+1)*var_length+1)/total_fitness;
proa= cumsum(parent_group(:,(var_num+1)*var_length+1));
prob= sort(rand(groupsize,1));
parent_num= 1;
child_num= 1;
while child_num<= groupsize
    if(prob(child_num)< proa(parent_num))
        select_group(child_num,:)= parent_group(parent_num,:);
        child_num= child_num+1;
    else
        parent_num= parent_num+1;
    end
end

function [child1,child2]= Cross(parent1,parent2,Pc,var_num,var_length,groupsize)
stringlength= var_num*var_length;
if(rand< Pc)
    cross_point= round(rand*(stringlength-2))+1;
    child1=[parent1(:,1:cross_point) parent2(:,cross_point+1:stringlength)];
    child2=[parent2(:,1:cross_point) parent1(:,cross_point+1:stringlength)];
    for k= 1:var_num
        child1(:,stringlength+k)= bi2de(child1(:,(k-1)*var_length+1:k*var_length));
        child2(:,stringlength+k)= bi2de(child2(:,(k-1)*var_length+1:k*var_length));
    end
    for k= 1:var_num
        child1(:,(var_num+1)*var_length+1)= Fun(child1(:,var_num*var_length+1:(var_num+1)*var_length));
        child2(:,(var_num+1)*var_length+1)= Fun(child2(:,var_num*var_length+1:(var_num+1)*var_length));
    end
else
    child1= parent1;
    child2= parent2;
end


function [child]= Mutation(parent,Pm,var_num,var_length)
stringlength= var_num*var_length;
if(rand< Pm)
    mutation_point= round(rand*(stringlength-1))+1;
    child= parent;
    child(mutation_point)= not(parent(mutation_point));
    for k= 1:var_num
        child(:,stringlength+k)= bi2de(child(:,(k-1)*var_length+1:k*var_length));
    end
    for k= 1:var_num
        child(:,(var_num+1)*var_length+1)= Fun(child(:,var_num*var_length+1:(var_num+1)*var_length));
    end
else
    child= parent;
end

[ 本帖最后由 eight 于 2007-11-18 22:31 编辑 ]

花如月

没有mat文件，别人用你的程序能跑起来么？

eight

我也一直搞不懂：你要别人帮你检查错误，你总得描述清楚、把所有信息给完整才行。真的不知道这是什么问题，智力水平？