matlab遗传算法优化

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;