NMinimize[f, x] minimizes f numerically with respect to x.NMinimize[f, {x, y, ...}] minimizes f numerically with respect to x, y, .... NMinimize[{f, cons}, {x, y, ...}] ...

Min[x_1, x_2, ...] yields the numerically smallest of the x_i. Min[{x_1, x_2, ...}, {y_1, ...}, ...] yields the smallest element of any of the lists.

ArgMin[f, x] gives a position x_min at which f is minimized.ArgMin[f, {x, y, ...}] gives a position {x_min, y_min, ...} at which f is minimized.ArgMin[{f, cons}, {x, y, ...}] ...

BooleanMinimize[expr] finds a minimal-length disjunctive normal form representation of expr.BooleanMinimize[expr, form] finds a minimal-length representation for expr in the ...

Searching for local minima and maxima. This finds the value of x which minimizes Γ(x), starting at x2. The last element of the list gives the value at which the minimum is ...

Building on its core symbolic architecture, Mathematica gives immediate access to the latest in industrial-strength Boolean computation. With highly general symbolic ...

MinValue[f, x] gives the minimum value of f with respect to x.MinValue[f, {x, y, ...}] gives the minimum value of f with respect to x, y, .... MinValue[{f, cons}, {x, y, ...

Integrated into Mathematica is a full range of state-of-the-art local and global optimization techniques, both numeric and symbolic, including constrained nonlinear ...

Mathematica uses a large number of original algorithms to provide automatic systemwide support for inequalities and inequality constraints. Whereas equations can often be ...

Mathematica's strengths in algebraic computation and graphics as well as numerics combine to bring unprecedented flexibility and power to geometric computation. Making ...