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FindMinimum

FindMinimum(f, {x, xstart})

searches for a local numerical minimum of f for the variable x and the start value xstart.

FindMinimum(f, {x, xstart}, Method->methodName)

searches for a local numerical minimum of f for the variable x and the start value xstart, with one of the following method names:

FindMinimum(f, {{x, xstart},{y, ystart},...})

searches for a local numerical minimum of the multivariate function f for the variables x, y,... and the corresponding start values xstart, ystart,....

See

Powell

Implements the Powell optimizer.

This is the default method, if no methodName is given.

ConjugateGradient

Implements the ConjugateGradient optimizer.
This is a derivative based method and the functions must be symbolically differentiable.

SequentialQuadratic

Implements the sequentiel quadratic optimizer.
This is a derivative, multivariate based method and the functions must be symbolically differentiable.

Examples

>> FindMinimum(Sin(x), {x, 0.5})
{-1.0,{x->-1.5708}}


>> FindMinimum(Sin(x)*Sin(2*y), {{x, 2}, {y, 2}}, Method -> "ConjugateGradient")
{-1.0,{x->1.5708,y->2.35619}}

FindMaximum, FindRoot, NRoots, Solve