close all;
clear all;
clc;
%--------------------初始化各参数值------------------------------------------------------
cecnum=1;
NP=100;
CRm=0.5;
G=500;
LP=100;
D=30;
a=-100;
b=100;
Aa=1;
A=[];
ikun1=0.25;
ikun2=0.25;
ikun3=0.25;
ikun4=0.25;
c=0;
t=0;
r=0;
l=0;
ck=0.000000001;
x=rand(NP,D)*(b-a)+a;        %随机生成初始种群
v=zeros(NP,D);
u=zeros(NP,D);
minx=99999;
best=0;
for i=1:NP                %求各个个体的适应度并取出适应度最好的个体的位置
    fit(i)=cec17(x(i,:),cecnum);
    if fit(i)<minx
        minx=fit(i);
        best=i;
    end
end
trace(1)=minx;
for g=1:G                %开始迭代
    best1=best;
    for i=1:NP
        F(i)=normrnd(0,0.33333)*0.1+0.4;                        %生成符合正态分布的F值
    end
    for i=1:NP
        CR(i)=normrnd(CRm,0.1);        %生成符合正态分布的CR值
    end
%--------------------变异操作----------------------------------------------------------------
    for m=1:NP
       num=randsrc(1,1,[1 2 3 4;ikun1 ikun2 ikun3 ikun4]);        %对选取的策略按照相应概率进行选取
       num1=randperm(NP,1);
       while num1==m
           num1=randperm(NP,1);
       end
       num2=randperm(NP,1);
       while (num2==m)||(num2==num1)
           num2=randperm(NP,1);
       end
       num3=randperm(NP,1);
       while (num3==m)||(num3==num1)||(num3==num2)
           num3=randperm(NP,1);
       end
        num4=randperm(NP,1);
       while (num4==m)||(num4==num1)||(num4==num2)||(num4==num3)
           num4=randperm(NP,1);
       end
       num5=randperm(NP,1);
       while (num5==m)||(num5==num1)||(num5==num2)||(num5==num3)||(num5==num4)
           num5=randperm(NP,1);
       end
       if num==1
           v(m,:)=x(num1,:)+F(m)*(x(num2,:)-x(num3,:));
       end
       if num==2
           v(m,:)=x(best,:)+F(m)*(x(num1,:)-x(num2,:))+F(m)*(x(num3,:)-x(num4,:));
       end
       if num==3
           v(m,:)=x(num1,:)+F(m)*(x(num2,:)-x(num3,:))+F(m)*(x(num4,:)-x(num5,:));
       end
       if num==4
           v(m,:)=x(m,:)+F(m)*(x(best,:)-x(m,:))+F(m)*(x(num1,:)-x(num2,:))+F(m)*(x(num3,:)-x(num4,:));
       end
%--------------------交叉操作--------------------------------------------------------
        for n=1:D
           cr=rand;
           if(cr<=CR(m))     
                u(m,n)=v(m,n);
           else
                u(m,n)=x(m,n);
           end
        end
%--------------------修补染色体--------------------------------------------------------  
        for n=1:D
            if u(m,n)<=a
                u(m,n)=a;
            end
            if u(m,n)>=b
                u(m,n)=b;
            end
        end
%--------------------重新求适应度，优胜劣汰----------------------
        fit1(m)=cec17(u(m,:),cecnum);
        if fit1(m)<fit(m)
            fit(m)=fit1(m);
            x(m,:)=u(m,:);
            A(1,Aa)=CR(m);
            Aa=Aa+1;
            if num==1
                c=c+1;
            end
            if num==2
                t=t+1;
            end
            if num==3
                r=r+1;
            end
            if num==4
                l=l+1;
            end
        end
        if fit1(m)<minx
            minx=fit1(m);
            best1=m;
        end
    end
    best=best1;
    trace(g+1)=minx;
%--------------------对CR进行自适应取值----------------------
    if mod(g,LP)==0
        if ~isempty (A)
            CRm=mean(A(:));                %求所有发生进化的个体所选用的CR的平均值
            clear A;
            A=[];
            Aa=1;
        end
        A=[];
        Aa=1;
%--------------------根据所选策略与其成功概率决定以后该策略的选取概率----------------------
        sk1=c/(LP*NP)+ck;
        sk2=t/(LP*NP)+ck;
        sk3=r/(LP*NP)+ck;
        sk4=l/(LP*NP)+ck;
        ikun1=sk1/(sk1+sk2+sk3+sk4);
        ikun2=sk2/(sk1+sk2+sk3+sk4);
        ikun3=sk3/(sk1+sk2+sk3+sk4);
        ikun4=sk4/(sk1+sk2+sk3+sk4);
        c=0;
        t=0;
        r=0;
        l=0;
    end
end
 
%--------------------结束迭代，绘制迭代次数与适应度的关系图----------------------
x(1,:);
figure(1);
plot(trace);
title(['差分进化算法(DE)','最小值','num2str(tt)']);
xlabel('迭代次数');
ylabel('目标函数值');