This is documentation for Mathematica 6, which was
based on an earlier version of the Wolfram Language.

# NMinimize

 NMinimize[f, {x, y, ...}]minimizes f numerically with respect to x, y, .... NMinimize[{f, cons}, {x, y, ...}]minimizes f numerically subject to the constraints cons.
• NMinimize returns a list of the form {fmin, {x->xmin, y->ymin, ...}}.
• cons can contain equations, inequalities or logical combinations of these.
• NMinimize always attempts to find a global minimum of f subject to the constraints given.
• By default, all variables are assumed to be real.
• can be used to specify that a variable can take on only integer values.
• If f and cons are linear, NMinimize can always find global minima, over both real and integer values.
• Otherwise, NMinimize may sometimes find only a local minimum.
• The following options can be given:
 AccuracyGoal Automatic number of digits of final accuracy sought EvaluationMonitor None expression to evaluate whenever f is evaluated MaxIterations 100 maximum number of iterations to use Method Automatic method to use PrecisionGoal Automatic number of digits of final precision sought StepMonitor None expression to evaluate whenever a step is taken WorkingPrecision MachinePrecision the precision used in internal computations
• The settings for AccuracyGoal and PrecisionGoal specify the number of digits to seek in both the value of the position of the maximum, and the value of the function at the minimum.
• Possible settings for the Method option include "NelderMead", "DifferentialEvolution", "SimulatedAnnealing" and "RandomSearch".
Find the global minimum of an unconstrained problem:
 Out[1]=
Extract the minimizing argument:
 Out[2]=

Find the global minimum of problems with constraints:
 Out[1]=
 Out[2]=
 Scope   (3)
 Options   (6)