www.pudn.com > GA.rar > SBOGA.m, change:2008-09-13,size:2571b


function [xv,fv] = SBOGA(fitness,a,b,NP,NG,q,Pc,Pm,eps) 
%顺序选择遗传算法 
L = ceil(log2((b-a)/eps+1));       %根据离散精度,确定二进制编码需要的码长 
 
x = zeros(NP,L); 
 
for i=1:NP 
     
    x(i,:) = Initial(L);                %种群初始化          
     
    fx(i) = fitness(Dec(a,b,x(i,:),L));  %个体适应值 
     
end 
 
for k=1:NG 
     
    [sortf,sortx] = sort(fx);            %适应值排序 
     
    x = x(sortx,:); 
     
    fx = fx(sortx); 
     
    for i=1:NP                           %固定选择概率 
         
        Px(i) = (1-q)^(NP-i)*q/(1-(1-q)^NP); 
         
    end 
     
    PPx = 0; 
     
    PPx(1) = Px(1); 
     
    for i=2:NP                        %用于轮盘赌策略的概率累加 
         
        PPx(i) = PPx(i-1) + Px(i); 
         
    end 
 
    for i=1:NP 
         
        sita = rand(); 
         
        for n=1:NP 
             
            if sita <= PPx(n) 
                 
                SelFather = n;           %根据轮盘赌策略确定的父亲 
                 
                break; 
                 
            end 
             
        end 
         
       Selmother = floor(rand()*(NP-1))+1;  %随机选择母亲 
         
        posCut = floor(rand()*(L-2)) + 1;     %随机确定交叉点 
         
        r1 = rand(); 
         
        if r1<=Pc                                     %交叉 
             
            nx(i,1:posCut) = x(SelFather,1:posCut); 
             
            nx(i,(posCut+1):L) = x(Selmother,(posCut+1):L); 
             
            r2 = rand(); 
             
            if r2 <= Pm                               %变异 
                 
                posMut = round(rand()*(L-1) + 1); 
                 
                nx(i,posMut) = ~nx(i,posMut); 
                 
            end 
             
        else 
             
            nx(i,:) = x(SelFather,:); 
             
        end 
         
    end 
 
    x = nx; 
     
    for i=1:NP 
         
        fx(i) = fitness(Dec(a,b,x(i,:),L));   %子代适应值 
         
    end 
     
end 
 
fv = -inf; 
 
for i=1:NP 
     
    fitx = fitness(Dec(a,b,x(i,:),L)); 
     
    if fitx > fv 
         
        fv = fitx;                                %取个体中的最好值作为最终结果 
         
        xv = Dec(a,b,x(i,:),L); 
         
    end 
     
end 
 
function result = Initial(length)         %初始化函数 
 
for i=1:length   
 
    r = rand(); 
 
    result(i) = round(r);    
 
end 
 
function y = Dec(a,b,x,L)         %二进制编码转换为十进制编码 
 
base = 2.^((L-1):-1:0); 
 
y = dot(base,x); 
 
y = a + y*(b-a)/(2^L-1);