Optimization with genetic algorithm in matlab - matlab

Question

I have written a simple optimization code using genetic algorithm.I don't know why I get error during running the code.Here is my code:
f = #(x1,x2) 1-x1.^2+(x1-x2).^2;
A = [1 1;-1 2;2 1];
b =[2 2 3]' ;
Aeq = [];
beq = [];
Lb = [0 0]';
Ub = [];
[Xopt,Fval] = ga(f,2,A,b,Aeq,beq,Lb,Ub)
I don not know why matlab gives me error.I wrote this programm based on the "Genetic algorithm Documentation" bit still gives me error:
Error using #(x1,x2)1-x1.^2+(x1-x2).^2
Not enough input arguments.
Error in createAnonymousFcn>#(x)fcn(x,FcnArgs{:}) (line 11)
fcn_handle = #(x) fcn(x,FcnArgs{:});
Error in makeState (line 48)
firstMemberScore = FitnessFcn(state.Population(initScoreProvided+1,:));
Error in galincon (line 18)
state = makeState(GenomeLength,FitnessFcn,Iterate,output.problemtype,options);
Error in ga (line 351)
[x,fval,exitFlag,output,population,scores] = galincon(FitnessFcn,nvars, ...
Caused by:
Failure in initial user-supplied fitness function evaluation. GA cannot continue

Answer 1

Objective functions of all optimization methods in MATLAB only accept 1 argument. According to ga documents:
fun — Objective function
Objective
function, specified as a function handle or function name. Write the
objective function to accept a row vector of length nvars and return a
scalar value.
When the 'UseVectorized' option is true, write fun to accept a
pop-by-nvars matrix, where pop is the current population size. In this
case, fun returns a vector the same length as pop containing the
fitness function values. Ensure that fun does not assume any
particular size for pop, since ga can pass a single member of a
population even in a vectorized calculation.
Change you objective function and it should work:
f = #(x) 1-x(1).^2+(x(1)-x(2)).^2;