fminsearch

Find the unconstrained minimum of a real function using the Nelder-Mead simplex algorithm.

Syntax

x = fminsearch(@func,x0)

x = fminsearch(@func,x0,options)

[x,fval,info,output] = fminsearch(...)

Inputs

func
The function to minimize.
x0
An estimate of the location of the minimum.
options
A struct containing option settings.
See optimset for details.

Outputs

x
The location of the function minimum.
fval
The minimum of the function.
info
The convergence status flag.
info = 1
Function value converged to within tolX.
info = 0
Reached maximum number of iterations or function calls.
output
A struct containing iteration details. The members are as follows:
iterations
The number of iterations.
nfev
The number of function evaluations.
xiter
The candidate solution at each iteration.
fvaliter
The objective function value at each iteration.

Examples

Minimize the Rosenbrock function.
function obj = Rosenbrock(x)
obj = (1 - x(1))^2 + 100 * (x(2) - x(1)^2)^2;
end

x0 = [-1.2, 1.0];
[x,fval] = fminsearch(@Rosenbrock, x0)
x = [Matrix] 1 x 2
1.00000  1.00000
fval = 5.29978e-14
Modify the previous example to pass an extra parameter to the user function using a function handle.
function obj = Rosenbrock2(x, offset)
obj = (1 - x(1))^2 + 100 * (x(2) - x(1)^2)^2 + offset;
end

handle = @(x) Rosenbrock2(x, 2);
[x,fval] = fminsearch(handle, interval)
x = [Matrix] 1 x 2
1.00000  1.00000
fval = 2