example5_5.m

MATLAB7辅助控制系统设计与仿真 第5章

function [x,endPop,bPop,traceInfo] = ga(bounds,eevalFN,eevalOps,startPop,opts,...
termFN,termOps,selectFN,selectOps,xOverFNs,xOverOps,mutFNs,mutOps)

n=nargin;
if n<2 | n==6 | n==10 | n==12
  disp('Insufficient arguements') 
end
if n<3 %Default eevalation opts.
  eevalOps=[];
end
if n<5
  opts = [1e-6 1 0];
end
if isempty(opts)
  opts = [1e-6 1 0];
end

if any(eevalFN<48) %Not using a .m file
  if opts(2)==1 %Float ga
    e1str=['x=c1; c1(xZomeLength)=', eevalFN ';'];  
    e2str=['x=c2; c2(xZomeLength)=', eevalFN ';'];  
  else %Binary ga
    e1str=['x=b2f(endPop(j,:),bounds,bits); endPop(j,xZomeLength)=',...
	eevalFN ';'];
  end
else %Are using a .m file
  if opts(2)==1 %Float ga
    e1str=['[c1 c1(xZomeLength)]=' eevalFN '(c1,[gen eevalOps]);'];  
    e2str=['[c2 c2(xZomeLength)]=' eevalFN '(c2,[gen eevalOps]);'];  
  else %Binary ga
    e1str=['x=b2f(endPop(j,:),bounds,bits);[x v]=' eevalFN ...
	'(x,[gen eevalOps]); endPop(j,:)=[f2b(x,bounds,bits) v];'];  
  end
end


if n<6 %Default termination information
  termOps=[100];
  termFN='maxGenTerm';
end
if n<12 %Default muatation information
  if opts(2)==1 %Float GA
  mutFNs=['boundaryMutation multiNonUnifMutation nonUnifMutation unifMutation'];
    mutOps=[4 0 0;6 termOps(1) 3;4 termOps(1) 3;4 0 0];
  else %Binary GA
    mutFNs=['binaryMutation'];
    mutOps=[0.05];
  end
end
if n<10    %默认的交叉信息
  if opts(2)==1    %浮点编码
    xOverFNs=['arithXover heuristicXover simpleXover'];
    xOverOps=[2 0;2 3;2 0];
  else %Binary GA
    xOverFNs=['simpleXover'];
    xOverOps=[0.6];
  end
end
if n<9 %Default select opts only i.e. roullete wheel.
  selectOps=[];
end
if n<8    %Default select info
  selectFN=['normGeomSelect'];
  selectOps=[0.08];
end
if n<6    %默认的算法终止准则
  termOps=[100];
  termFN='maxGenTerm';
end
if n<4    %初始种群为空
  startPop=[];
end
if isempty(startPop)    %随机生成初始种群
  startPop=initializega(80,bounds,eevalFN,eevalOps,opts(1:2));
end

if opts(2)==0    %二进制编码
  bits=calcbits(bounds,opts(1));
end

xOverFNs=parse(xOverFNs);
mutFNs=parse(mutFNs);

xZomeLength  = size(startPop,2); 	%Length of the xzome=numVars+fittness
numVar       = xZomeLength-1;    %变量数目
popSize      = size(startPop,1);            %种群中个体数目
endPop       = zeros(popSize,xZomeLength);    %次种群矩阵
c1           = zeros(1,xZomeLength); 	     %个体
c2           = zeros(1,xZomeLength); 		%个体
numXOvers    = size(xOverFNs,1); 			%交叉操作次数
numMuts      = size(mutFNs,1); 			%变异操作次数
epsilon      = opts(1);                 		%适应度门限值
oeval         = max(startPop(:,xZomeLength)); %初始种群中的最优值
bFoundIn     = 1;
done         = 0;
gen          = 1;
collectTrace = (nargout>3);
floatGA      = opts(2)==1;
display      = opts(3);

while(~done)
  [beval,bindx] = max(startPop(:,xZomeLength));     %当前种群的最优值
  best =  startPop(bindx,:);

  if collectTrace
    traceInfo(gen,1)=gen; 		          %当前代
    traceInfo(gen,2)=startPop(bindx,xZomeLength);       %最优适应度
    traceInfo(gen,3)=mean(startPop(:,xZomeLength));     %平均适应度
    traceInfo(gen,4)=std(startPop(:,xZomeLength)); 
  end
  
  if ( (abs(beval - oeval)>epsilon) | (gen==1)) 
    if display
      fprintf(1,'\n%d %f\n',gen,beval);          
    end
    if floatGA
      bPop(bFoundIn,:)=[gen startPop(bindx,:)]; 
    else
      bPop(bFoundIn,:)=[gen b2f(startPop(bindx,1:numVar),bounds,bits)...
	  startPop(bindx,xZomeLength)];
    end
    bFoundIn=bFoundIn+1;                    
    oeval=beval;                               
  else
    if display
      fprintf(1,'%d ',gen);	              
    end
  end
  
  endPop = feeval(selectFN,startPop,[gen selectOps]);    %选择操作
  
  if floatGA 
    for i=1:numXOvers,
      for j=1:xOverOps(i,1),
	a = round(rand*(popSize-1)+1);    %一个父代个体
	b = round(rand*(popSize-1)+1);    %另一个父代个体
	xN=deblank(xOverFNs(i,:));   %交叉函数
	[c1 c2] = feeval(xN,endPop(a,:),endPop(b,:),bounds,[gen… xOverOps(i,:)]);
	
	if c1(1:numVar)==endPop(a,(1:numVar)) 
	  c1(xZomeLength)=endPop(a,xZomeLength); 
	elseif c1(1:numVar)==endPop(b,(1:numVar))
	  c1(xZomeLength)=endPop(b,xZomeLength);
	else 
	  eeval(e1str);
	end
	if c2(1:numVar)==endPop(a,(1:numVar))
	  c2(xZomeLength)=endPop(a,xZomeLength);
	elseif c2(1:numVar)==endPop(b,(1:numVar))
	  c2(xZomeLength)=endPop(b,xZomeLength);
	else 
	  eeval(e2str);
	end      
	
	endPop(a,:)=c1;
	endPop(b,:)=c2;
      end
    end
  
    for i=1:numMuts,
      for j=1:mutOps(i,1),
	a = round(rand*(popSize-1)+1);
	c1 = feeval(deblank(mutFNs(i,:)),endPop(a,:),bounds,[gen mutOps(i,:)]);
	if c1(1:numVar)==endPop(a,(1:numVar)) 
	  c1(xZomeLength)=endPop(a,xZomeLength);
	else
	  eeval(e1str);
	end
	endPop(a,:)=c1;
      end
    end
    
  else    %遗传操作的统计模型
    for i=1:numXOvers,
      xN=deblank(xOverFNs(i,:)); 	
      cp=find(rand(popSize,1)<xOverOps(i,1)==1);
      if rem(size(cp,1),2) cp=cp(1:(size(cp,1)-1)); end
      cp=reshape(cp,size(cp,1)/2,2);
      for j=1:size(cp,1)
	 a=cp(j,1); b=cp(j,2); 
	 [endPop(a,:) endPop(b,:)] = feeval(xN,endPop(a,:),endPop(b,:), bounds,[gen xOverOps(i,:)]);
      end
    end
    for i=1:numMuts
      mN=deblank(mutFNs(i,:));
      for j=1:popSize
	   endPop(j,:) = feeval(mN,endPop(j,:),bounds,[gen mutOps(i,:)]);
	   eeval(e1str);
      end
    end
  end
  
  gen=gen+1;
  done=feeval(termFN,[gen termOps],bPop,endPop); %
  startPop=endPop; 			%更新种群
  
  [beval,bindx] = min(startPop(:,xZomeLength)); 
  startPop(bindx,:) = best; 		
end

[beval,bindx] = max(startPop(:,xZomeLength));
if display 
  fprintf(1,'\n%d %f\n',gen,beval);	  
end

x=startPop(bindx,:);
if opts(2)==0 %binary
    x=b2f(x,bounds,bits);
bPop(bFoundIn,:)=[gen b2f(startPop(bindx,1:numVar),bounds,bits), startPop(bindx,xZomeLength)];
else
  bPop(bFoundIn,:)=[gen startPop(bindx,:)];
end
if collectTrace
  traceInfo(gen,1)=gen; 		
  traceInfo(gen,2)=startPop(bindx,xZomeLength); %Best fittness
  traceInfo(gen,3)=mean(startPop(:,xZomeLength)); %Avg fittness
end