resuming and starting from new line in genetic algorithm after specific generations

2 次查看（过去 30 天）

显示更早的评论

Hamid 2014-11-5

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/161438-resuming-and-starting-from-new-line-in-genetic-algorithm-after-specific-generations

评论： Hamid 2014-11-14

Hi,

I want to resume and start from new line in genetic algorithm after specific generations.

Has anyone know How is impossible??

Any suggestion may help a lot.

Thank you guys.

7 个评论
显示 5更早的评论隐藏 5更早的评论

Hamid 2014-11-9

编辑：Hamid 2014-11-9

在 MATLAB Online 中打开

I want to change f-matrix every 100 generations and I'm partly sure that a solution better happen at the end of generation 700, beside I don't have another choice and I have to inject all these 7 conditions.

for example : nn=20 nb=4 nl=6
case 1 (0-100 generations) : f(13)=800 f(14)=0 f(15)=-1000 and so on
case 2 (101-200 generations) : f(13)=0 f(14)=700 f(15)=-500 and so on

also I used 5 for an experiment and the right one is 700 generations.

Thank you very much Geoff for helping me.

Hamid 2014-11-9

Dear Geoff - my final goal is to reaching to best solution under all 7 conditions together, these conditions only difference in f-matrix.

What do you recommend?????

I'm so confused and I'm gonna be crazy.

请先登录，再进行评论。

请先登录，再回答此问题。

回答（1 个）

Geoff Hayes 2014-11-10

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/161438-resuming-and-starting-from-new-line-in-genetic-algorithm-after-specific-generations#answer_158342

在 MATLAB Online 中打开

Hamid - I don't think that I can give a valid recommendation because I don't know enough of what you are trying to do. f seems to be a matrix used in the fitness function, but I can't guess as to its impact or that of changing a handful of its values. But if you want to try and re-use the population after 100 iterations with a slight change to the f matrix, then you could change your return from the ga function of

[x,fval]=ga(@(x) penalty2(x,available,bc,Dof,E...),Nvars,options);

 [x,fval,exitflag,output,population] = ga(@(x)penalty2(x,available,bc,Dof, E...),Nvars,options);

The population output parameter will be the final population for (say) 100 iterations of the algorithm. You then update the f matrix, and re-call

 % re-use the population as the initial population for the next 100 generations
 options = gaoptimset('InitialPopulation', population);
 % run the algorithm
 [x,fval,exitflag,output,population] = ga(@(x)penalty2(x,available,bc,Dof, E...),Nvars,options);

for 100 more generations. Then change f to whatever you want. You can put this in a loop that iterates from 1 through to 7, and you would change f on each iteration.

However, this method may not work as expected especially if the GA has converged to a premature solution before generation 100. If all members of the population are identical (or near-identical) then there will not be enough genetic diversity in the next round of 100 generations to produce any new members even though you have changed the f matrix.

19 个评论
显示 17更早的评论隐藏 17更早的评论

Hamid 2014-11-11

在 MATLAB Online 中打开

Dear Geoff - you were right and popSize and Initpop are the same size.

I know what you saying but I can't fulfill it correctly.

these are my codes with new changes :

[x,fval,exitflag,output,popSize] = ga(@(x) penalty2(x,available,bc,Dof,E,f,fixedcoord,na,nb,neft,nevt,nl,nn,numbitCoordX,numbitCoordY,numbitCoordZ,numbitEdof,numbitEp,sq,TOPGSM,xspan,yspan,zspan),Nvars,options);
Time=toc;
   % re-use the population as the initial population for the next 100 generations
   options = gaoptimset('InitialPopulation', popSize);
   f=zeros(3*nn,1);
  for i=nb+1:nb+nl
      f(3*i-2)=input(['For load node ',num2str(i-nb),' please specify the X-resultant of the load! (N) ']);
      f(3*i-1)=input(['For load node ',num2str(i-nb),' please specify the Y-resultant of the load! (N) ']);
      f(3*i)=input(['For load node ',num2str(i-nb),' please specify the Z-resultant of the load! (N) ']);
  end 
   % run the algorithm
  [x,fval,exitflag,output,popSize] = ga(@(x) penalty2(x,available,bc,Dof,E,f,fixedcoord,na,nb,neft,nevt,nl,nn,numbitCoordX,numbitCoordY,numbitCoordZ,numbitEdof,numbitEp,sq,TOPGSM,xspan,yspan,zspan),Nvars,options);

but I kept this error again :

??? Error using ==> bin2dec at 36
Binary string must be 52 bits or less.

please write the codes for me.

You are the best Geoff, thanks a lot.

Hamid 2014-11-12

在 MATLAB Online 中打开

??? Error using ==> bin2dec at 36
Binary string must be 52 bits or less.
Error in ==> bintranslate at 137
    if ceil(bin2dec(num2str(chromosome4(i-(numbitEp-1):i))))>na
Error in ==> penalty2 at 38
[Coord,Edof2,Ep2]=bintranslate(available,chromosome,Dof,fixedcoord,na,nb,neft,nevt,nl,nn,numbitCoordX,numbitCoordY,numbitCoordZ,numbitEdof,numbitEp,xspan,yspan,zspan);
Error in ==>
GAmodule>@(x)penalty2(x,available,bc,Dof,E,f,fixedcoord,na,nb,neft,nevt,nl,nn,numbitCoordX,numbitCoordY,numbitCoordZ,numbitEdof,numbitEp,sq,TOPGSM,xspan,yspan,zspan)
at 177
[x,fval,exitflag,output,popSize] = ga(@(x)
penalty2(x,available,bc,Dof,E,f,fixedcoord,na,nb,neft,nevt,nl,nn,numbitCoordX,numbitCoordY,numbitCoordZ,numbitEdof,numbitEp,sq,TOPGSM,xspan,yspan,zspan),Nva
Error in ==> validate>@(x)fitness(x,FitnessFcnArgs{:}) at 135
    fitness = @(x) fitness(x,FitnessFcnArgs{:});
Error in ==> fcnvectorizer at 14
            y(i,:) = feval(fun,(pop(i,:)));
Error in ==> stepGA at 45
    nextScore = fcnvectorizer(nextPopulation,FitnessFcn,1,options.SerialUserFcn);
Error in ==> gaunc at 85
            [score,population,state] = stepGA(score,population,options,state,GenomeLength,FitnessFcn);
Error in ==> ga at 279
        [x,fval,exitFlag,output,population,scores] = gaunc(FitnessFcn,nvars, ...
Error in ==> GAmodule at 177
[x,fval,exitflag,output,popSize] = ga(@(x)
penalty2(x,available,bc,Dof,E,f,fixedcoord,na,nb,neft,nevt,nl,nn,numbitCoordX,numbitCoordY,numbitCoordZ,numbitEdof,numbitEp,sq,TOPGSM,xspan,yspan,zspan),Nva
Caused by:
    Failure in user-supplied fitness function evaluation. GA cannot continue.

Geoff Hayes 2014-11-14

Hamid - you will have to work backwards from the above in order to determine what the problem is. Consider how nevt and neft are initialized and/or updated.

Hamid 2014-11-14