# Wolfram Language & System 10.4 (2016)|Legacy Documentation

This is documentation for an earlier version of the Wolfram Language.
BUILT-IN WOLFRAM LANGUAGE SYMBOL

# ArgMin

ArgMin[f,x]
gives a position at which f is minimized.

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

ArgMin[{f,cons},{x,y,}]
gives a position at which f is minimized subject to the constraints cons.

ArgMin[,xreg]
constrains x to be in the region reg.

ArgMin[,,dom]
constrains variables to the domain dom, typically Reals or Integers.

## Details and OptionsDetails and Options

• ArgMin returns a list of the form .
• ArgMin[,{x,y,},] is effectively equivalent to {x,y,}/.Last[Minimize[,{x,y,},].
• cons can contain equations, inequalities or logical combinations of these.
• The constraints cons can be any logical combination of:
•  lhs==rhs equations lhs!=rhs inequations or inequalities {x,y,…}∈reg region specification Exists[x,cond,expr] existential quantifiers
• If f and cons are linear or polynomial, ArgMin will always find a global minimum.
• ArgMin[{f,cons},xreg] is effectively equivalent to ArgMin[{f,consxreg},x].
• For , the different coordinates can be referred to using Indexed[x,i].
• ArgMin will return exact results if given exact input.
• If ArgMin is given an expression containing approximate numbers, it automatically calls NArgMin.
• If the minimum is achieved only infinitesimally outside the region defined by the constraints, or only asymptotically, ArgMin will return the closest specifiable point.
• If no domain is specified, all variables are assumed to be real.
• xIntegers can be used to specify that a particular variable can take on only integer values.
• If the constraints cannot be satisfied, ArgMin returns .
• N[ArgMin[]] calls NArgMin for optimization problems that cannot be solved symbolically.

## ExamplesExamplesopen allclose all

### Basic Examples  (5)Basic Examples  (5)

Find a minimizer point for a univariate function:

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Find a minimizer point for a multivariate function:

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Find a minimizer point for a function subject to constraints:

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Find a minimizer point as a function of parameters:

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Find a minimizer point over a geometric region:

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Plot it:

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