MATLAB: I’m getting followig errors when options are used in ga solver

gagaoptimsetoptions in ga

main function

clear all
clc
nvars=3;
lb=[6 2 2];
ub=[100 4 4];
options = gaoptimset('PlotFcns',{@gaplotbestf,@gaplotmaxconstr},'Display','iter');
[x, fval,exitflag,output,population]=ga(@my_fun,nvars,[],[],[],[],lb,ub,options)

error when using options

Error using functionHandleOrCell (line 13)
The constraint function must be a function handle.
Error in validate (line 156)
      [nonlcon,NonconFcnArgs] = functionHandleOrCell('NonconFcn',nonlcon);
Error in gacommon (line 72)
[options,nvars,FitnessFcn,NonconFcn] =
validate(options,type,nvars,fun,nonlcon,user_options);
Error in ga (line 319)
[x,fval,exitFlag,output,population,scores,FitnessFcn,nvars,Aineq,bineq,Aeq,beq,lb,ub, ...
Error in start (line 7)
[x, fval,exitflag,output,population]=ga(@my_fun,nvars,[],[],[],[],lb,ub,options)

Best Answer

Is "The constraint function must be a function handle." a valuable hint?

Related Solutions

MATLAB: I’m getting Error using ga (line 305) help me

Arunachalam - the error message is telling you that the tenth parameter/argument to the ga function is not the options object that should be created with the gaoptimset function. Instead, the tenth argument corresponds to UB, the array of upper bounds. If you look at the documentation for ga you will not that you are passing too many input parameters/arguments for what you have in mind. Your call to ga should be reduced to (according to the 2015a documentation)

 x = ga(@my_fun,nvars,[],[],[],[],LB,UB,@const);

Note that you may also want to review the nonlcon documentation as it would appear that this function (your const) should return two outputs).

MATLAB: Hello everyone! this is the first time I am using GA and I encountered with this message:Failure in initial user-supplied fitness function evaluation. GA cannot continue.

amir - you don't need to supply the f, those f values that have been attained in another code. The genetic algorithm will provide those from the initial population and from the subsequent generations (via crossover and mutation). All you need to do is pass in the function handle like

[x,fval] = ga(@myfcn, 3)

Since your myfcn depends upon the k1, k2, and k3, then ensure that your fitness function is nested within the main function

function main
    k1=0.6;
    k2=0.25;
    k3=0.15;
         
    [x,fval] = ga(@myfcn,3)
             
    function t=myfcn(f)
        t=(k1*f(1)+k2*f(2)+k3*f(3));
    end
end

and saved (in this case) to a file named main.m. (Perhaps you have already done this.)

Best Answer

Related Solutions

MATLAB: I’m getting Error using ga (line 305) help me

MATLAB: Hello everyone! this is the first time I am using GA and I encountered with this message:Failure in initial user-supplied fitness function evaluation. GA cannot continue.

Related Question