fitnessfcn: Not enough input arguments.

function Y = objfun(X)

% Y = fitness value

% X = variable vector (1*n)

% R = 1.994*r^-0.32*f^2.34*v^-0.01*d^0.18

% where r=[0.2:0.8], f=[0.2:0.6], v=[39.27:117.81], d=[0.2:0.8]

r=X(1,1); % variable 1

f=X(1,2); % variable 2

v=X(1,3); % variable 3

d=X(1,4); % variable 4

Y = 1.994*r^-0.32*f^2.34*v^-0.01*d^0.18;

Answer 1

[Ameer Hamza]

I think you are trying to run this function by pressing the Green Run button. It will not work because you can not specifying the value of X. Call it like this, from the command window or a script

X = [2 1 4 5]; % example values
objfun(X)

[ANIL KUMAR K]

not able to solve by this answer

Answer 2

[Star Strider]

It would help to see your ga call.

When I run your function using this ga call:

Xest = ga(@objfun, 4)

it produces (in one run):

Xest =
      -355.83     0.028458       181.05    -0.038601

Be certain that you are providing the correct value (4) for ‘nvars’ , or if you are using InitialPopulationMatrix that the matrix has 4 columns.

[ANIL KUMAR K]

Xest = ga(@objfun, 4)

Optimization terminated: average change in the fitness value less than options.TolFun.

Xest =

4.8324 0.0009 4.0761 0.0058

I got above values

[Star Strider]

The point is that your code no longer throws the error!

The values will likelly not be the same (at least exactly the same) on any specific run, unless the tolerances are decreased. (Use optimoptions to set them.)

It is generally necessary to use the values returned by ga that have the lowest fitness score (include the ‘fval’ output to return and display them) as starting parameter estimates for fminsearch or fminunc, or similar functions. Those functions will generally provide more precise parameter estimates, however the ga results with the lowest fitness scores are the best initial values to provide to them.

If my Answer helped you solve your problem, please Accept it!

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