I'm trying to run this program through Optimtool but getting the errors - "Undefined function 'symsum' for input arguments of type double". Can somebody help me with this code?

Attached Picture is the actual question. I want to perform a Simulated Annealing algorithm on this question to find the number of iterations occurring before reaching the final value. Here is the code that I wrote -

 function y = SAcode(N)
syms i
y = symsum((N(1)-3).^2+(N(2).^(i)-3).^2 +(N(3).^(i)-3).^2,i,1,N(1));
end
ObjectiveFunction = @SAcode;
n = [2 2.4 3.6];
lb = [1 1 1];
ub = [5 5 5];
[N,fval,exitFlag,output] = simulannealbnd(ObjectiveFunction,n,lb,ub);
fprintf('The number of iterations was : %d\n', output.iterations);
fprintf('The number of function evaluations was : %d\n', output.funccount);
fprintf('The best function value found was : %g\n', fval);

Answer 1

[madhan ravi]

>> N =[20:23]

syms k
y = symsum((N(1)-3).^2+(N(2).^(K)-3).^2 +(N(3).^(K)-3).^2,K,1,N(1));

N =

      20    21    22    23

>> y

y =

576242485144297694059340321398556670349680706722787840

>>

[madhan ravi]

The above shows an example but I didn't get any trouble getting the result

[Aditya Banerjee]

But when I'm trying to run the same function for Simulated Annealing, it is giving me the error. The attached picture is what I'm getting.

[madhan ravi]

I think symbolic operations are not allowed in optimisation maybe try:

N =[20:23]
K=1:N(1)
y = cumsum((N(1)-3).^2+(N(2).^(K)-3).^2 +(N(3).^(K)-3).^2);

y(end)

[Aditya Banerjee]

Yeah. It finally ran. Thank you so much.

[Aditya Banerjee]

The program did ran, but in the output I found that only two values of N are displayed. What could be the explanation for that?

[madhan ravi]

Two values of N are displayed

I don’t understand , mind explaining?

[Aditya Banerjee]

This is what I got in output.

Optimization terminated: change in best function value less than options.FunctionTolerance.
The number of iterations was : 1000
The number of function evaluations was : 1009
The best function value found was : 5
>> [N,fval,exitFlag,output] = simulannealbnd(ObjectiveFunction,n,lb,ub)
Optimization terminated: change in best function value less than options.FunctionTolerance.

N =

    2.4000    3.6000

fval =

     5

exitFlag =

     1

[madhan ravi]

I don’t have any experience with optimisation so my knowledge is limited in this field sorry

[Aditya Banerjee]

No problem. Thank you so much for the rectification.

[madhan ravi]

Anytime :) glad that I could help