fminsearch

Unconstrained derivative-free minimization.

📝Syntax

x = fminsearch(fun, x0)
[x, fval, exitflag, output] = fminsearch(fun, x0, options)
x = fminsearch(problem)

📥Input Arguments

Parameter	Description
fun	function handle or function name returning a scalar value.
x0	initial point.
options	structure or solver options created with optimset or optimoptions.

📤Output Arguments

Parameter	Description
x	estimated minimizer.
fval	objective value at x.
exitflag	positive on convergence, zero on iteration or evaluation limit, negative when stopped by a callback.
output	diagnostic structure.

📄Description

fminsearch uses the Nelder-Mead simplex method. Supported controls include TolX, TolFun, MaxIter, MaxFunEvals, Display, OutputFcn and PlotFcns. A problem structure can contain objective, x0 and options fields.

💡Examples

opts = optimset('TolX', 1e-8, 'TolFun', 1e-8);
[x, fval] = fminsearch(@(x) (x(1) - 1)^2 + (x(2) + 2)^2, [0 0], opts)

🔗See Also

fminbnd optimset

Used Functions

optimset optimoptions

📚Bibliography

J. A. Nelder and R. Mead, "A simplex method for function minimization", The Computer Journal, 1965. J. C. Lagarias, J. A. Reeds, M. H. Wright and P. E. Wright, "Convergence properties of the Nelder-Mead simplex method in low dimensions", SIAM Journal on Optimization, 1998.

🕔Version History

Version	Description
2.0.0	initial version

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