编程实现利用遗传算法求解方程最值.doc

编程实现利用遗传算法求解方程最值一 函数为：求函数y=x+3*sin(2*x)-7*cos(x) 在【-4 4】的最大值二 MATLAB 程序如下：1.主控制程序GA.m%求函数y=x+3*sin(2*x)-7*cos(x) 在【-4 4】的最大值%function main()clearclcpopsize=100 chromlength=10pc=0.6 pm=0.01%pop=initpop(popsize,chromlength) for i=1:100 objvalue=calobjvalue(pop) fitvalue=calfitvalue(objvalue) newpop=selection(pop,fitvalue)%选择操作 newpop=crossover(pop,pc)%交叉操作 newpop=mutation(pop,pm)%变异操作 bestindividaul,bestfit=best(pop,fitvalue)%求出群体中适应值最大的个体及其适应值 y(i)=max(bestfit) n(i)=i pop5=bestindividaul x(i)=decodechrom(pop5,1,chromlength)*8/1023-4 pop=newpop;endx(i)y(i)fplot(x+3*sin(2*x)-7*cos(x),-4 4)grid onhold on plot(x,y,r*)title(x+3*sin(2*x)-7*cos(x)的最大值)hold off2.子程序：初始化%初始化function pop=initpop(popsize,chromlength)pop=round(rand(popsize,chromlength) %rand随机产生初始种群3. 子程序：计算目标函数%计算目标函数值function objvalue=calobjvalue(pop)temp1=decodechrom(pop,1,10) x=temp1*8/1023-4 objvalue=x+3*sin(2*x)-7*cos(x)function pop2=decodechrom(pop,spoint,length)pop1=pop(:,spoint:spoint+length-1)pop2=decodebinary(pop1)function pop2=decodebinary(pop)px,py=size(pop)for i=1:py pop1(:,i)=2.(py-1).*pop(:,i) py=py-1endpop2=sum(pop1,2)4. 子程序：选择操作%选择function newpop=selection(pop,fitvalue)totalfit=sum(fitvalue) fitvalue=fitvalue/totalfit%但个个体选择概率fitvalue=cumsum(fitvalue)px,py=size(pop)ms=sort(rand(px,1)fitin=1newin=1 while newin=px if(ms(newin)fitvalue(fitin) newpop(newin,:)=pop(fitin,:) newin=newin+1 else fitin=fitin+1 end end5.子程序：交叉% 交叉function newpop=crossover(pop,pc)px,py=size(pop)newpop=ones(size(pop)for i=1:2:px-1 if(randpc) cpoint=round(rand*py) newpop(i,:)=pop(i,1:cpoint) pop(i+1,cpoint+1:py) newpop(i+1,:)=pop(i+1,1:cpoint) pop(i,cpoint+1:py) else newpop(i,:)=pop(i,:) newpop(i+1,:)=pop(i+1,1) endend%6. 子程序：变异%变异function newpop=mutation(pop,pm)px,py=size(pop)newpop=ones(size(pop)for i=1:px if(randpm) mpoint=round(ra