遗传算法实现收获系统最优控制

以下为用遗传算法实现离散系统收获控制系统的MATLAB代码程序种群采用十进制表示，且有8个子种群，每个子种群有20个变量，其中考虑了在一定代数之后的子种群间的迁移率。NIND=20;NVAR=20;MAXGEN=200;GGAP=0.8;MUTR=1/NVAR;INSR=0.9;SUBPOP=8;MIGR=0.2;MIGGEN=20;RANGE=[0;200]FieldDD=rep(RANGE,[1,NVAR]);gen=1;trace二zeros(MAXGEN,2);%是两列，MAXGEN行Chrom=crtrp(NIND*SUBPOP,FieldDD)Objv=objharv(Chrom);gen=1;whilegen<=MAXGENFitv=ranking(Objv,[2,1],SUBPOP);Sel=select('sus',Chrom,Fitv,GGAP);Sel=recombin('recdis',Sel,1,SUBPOP);Sel=mutate('mutbga',Sel,FieldDD,MUTR,SUBPOP);Objvsel=objharv(Sel)[Chrom,Objv]=reins(Chrom,Sel,SUBPOP,[1,INSR],Objv,Objvsel);trace(gen,1)=min(Objv);trace(gen,2)=sum(Objv)/length(Objv);if(rem(gen,MIGGEN)==20)[Chrom,Objv]=migrate(Chrom,SUBPOP,[MIGR,1,1],Objv);endgen=gen+1;end[Y,I]=min(Objv);figure(1)plot(Chrom(l,:),'bo');%画出最后种群对应最小目标函数值的那一行的个体变量值figure(2)plot(trace(:,1));holdonplot(trace(:,2),'.')gridlegend('解的变化','平均值的变化')functionObjVal=objharv(Chrom,rtn_type);%DimensionofobjectivefunctionDim=20;%valuesfromMICHALEWICZa=1.1;x0=100;xend=x0;XENDWEIGHT=0.4/(Dim96);%Computepopulationparameters[Nind,Nvar]=size(Chrom);%ChecksizeofChromanddotheappropriatething%ifChromis[],thendefinesizeofboundary-matrixandvaluesifNind==0%returntextoftitleforgraphicoutputifrtn_type==2ObjVal=['HARVESTPROBLEM-'int2str(Dim)];%returnvalueofglobalminimumelseifrtn_type==3ObjVal=-sqrt(x0*(aADim-1)A2/(aA(Dim-1)*(a-1)));%definesizeofboundary-matrixandvalueselse%lowerandupperbound,identicalforallnvariablesObjVal1=[0;10*Dim];ObjVal=rep(ObjVal1,[1Dim]);end%ifDimvariables,computevaluesoffunctionelseifNvar==DimObjVal=zeros(Nind,1);X=rep(x0,[Nind1]);forirun=1:Nvar,X=a*X-Chrom(:,irun);endX;ObjVal=-(sum(sqrt(Chrom)')'-XENDWEIGHT*abs(X-x0));%otherwiseerror,wrongformatofChromelseerror('sizeofmatrixChromisnotcorrectforfunct