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Points in the domain of definition of a real-valued function at which it takes its greatest and smallest values; such points are also called absolute maximum and absolute minimum points. If <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m0630801.png" /> is defined on a topological space <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m0630802.png" />, then a point <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m0630803.png" /> is called a local maximum (local minimum) point if there is a neighbourhood <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m0630804.png" /> of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m0630805.png" /> such that <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m0630806.png" /> is an absolute maximum (minimum) point for the restriction of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m0630807.png" /> to this neighbourhood. One distinguishes between strict and non-strict maximum (minimum) points (both absolute and local). For example, a point <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m0630808.png" /> is called a non-strict (strict) local maximum point of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m0630809.png" /> if there is a neighbourhood <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308010.png" /> of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308011.png" /> such that for all <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308012.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308013.png" /> (<img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308014.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308015.png" />).
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For functions defined on finite-dimensional domains there are conditions and tests, in terms of differential calculus, for a given point to be a local maximum (minimum) point. Let <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308016.png" /> be defined in a neighbourhood of a point <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308017.png" /> of the real line. If <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308018.png" /> is a non-strict local maximum (minimum) point and if the derivative <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308019.png" /> exists, then the latter is equal to zero.
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{{TEX|done}}
  
If a function <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308020.png" /> is differentiable in a neighbourhood of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308021.png" /> except, possibly, at <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308022.png" /> itself where it is continuous, and if the derivative <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308023.png" /> is of constant sign on each side of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308024.png" /> in this neighbourhood, then for <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308025.png" /> to be a strict local maximum (local minimum) point it is necessary and sufficient that the derivative changes sign from plus to minus, that is, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308026.png" /> for <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308027.png" /> and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308028.png" /> for <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308029.png" /> (respectively, from minus to plus; <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308030.png" /> for <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308031.png" /> and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308032.png" /> for <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308033.png" />). However, it is not possible to speak of the change of sign of the derivative at <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308034.png" /> for every function <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308035.png" /> that is differentiable in a neighbourhood of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308036.png" />.
+
Points in the domain of definition of a real-valued function at which it takes its greatest and smallest values; such points are also called absolute maximum and absolute minimum points. If  $  f $
 +
is defined on a topological space  $  X $,  
 +
then a point  $  x _ {0} $
 +
is called a local maximum (local minimum) point if there is a neighbourhood  $  U \subseteq X $
 +
of  $  x _ {0} $
 +
such that $  x _ {0} $
 +
is an absolute maximum (minimum) point for the restriction of  $  f $
 +
to this neighbourhood. One distinguishes between strict and non-strict maximum (minimum) points (both absolute and local). For example, a point  $  x _ {0} \in \mathbf R $
 +
is called a non-strict (strict) local maximum point of $  f $
 +
if there is a neighbourhood  $  U $
 +
of $  x _ {0} $
 +
such that for all  $  x \in U $,
 +
$  f ( x) \leq  f ( x _ {0} ) $(
 +
$  f( x) < f ( x _ {0} ) $,
 +
$  x \neq x _ {0} $).
  
If <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308037.png" /> has <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308038.png" /> derivatives at <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308039.png" /> and if <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308040.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308041.png" />, <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308042.png" />, then for <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308043.png" /> to be a strict local maximum point it is necessary and sufficient that <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308044.png" /> be even and that <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308045.png" />, and for a local minimum that <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308046.png" /> be even and <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308047.png" />.
+
For functions defined on finite-dimensional domains there are conditions and tests, in terms of differential calculus, for a given point to be a local maximum (minimum) point. Let  $  f $
 +
be defined in a neighbourhood of a point  $  x _ {0} $
 +
of the real line. If  $  x _ {0} $
 +
is a non-strict local maximum (minimum) point and if the derivative  $  f ^ { \prime } ( x _ {0} ) $
 +
exists, then the latter is equal to zero.
  
Let <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308048.png" /> be defined in an <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308049.png" />-dimensional neighbourhood of a point <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308050.png" /> and let it be differentiable at this point. If <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308051.png" /> is a non-strict local maximum (minimum) point, then the differential of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308052.png" /> at this point is equal to zero. This condition is equivalent to all first-order partial derivatives of <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308053.png" /> being zero at this point. If the function has continuous second-order partial derivatives at <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308054.png" />, if all its first-order derivatives are equal to zero at <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308055.png" />, and if the second-order differential at <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308056.png" /> is a negative-definite (positive-definite) quadratic form, then <img align="absmiddle" border="0" src="https://www.encyclopediaofmath.org/legacyimages/m/m063/m063080/m06308057.png" /> is a strict local maximum (minimum) point. Conditions for maximum and minimum points of differentiable functions are known when restrictions are imposed on the variation of the arguments in the domain: coupling equations must be satisfied. Necessary and sufficient conditions for a maximum (minimum) of a real-valued function with a more complicated structure of its domain of definition have been obtained in special areas of mathematics; for example, in [[Convex analysis|convex analysis]] and [[Mathematical programming|mathematical programming]] (see also [[Maximization and minimization of functions|Maximization and minimization of functions]]). Maximum and minimum points of functions on manifolds are studied in [[Variational calculus in the large|variational calculus in the large]], and maximum and minimum points for functions on function spaces, that is, for functionals, are studied in [[Variational calculus|variational calculus]]. There are also various numerical approximation methods for finding maximum and minimum points.
+
If a function  $  f $
 +
is differentiable in a neighbourhood of  $  x _ {0} $
 +
except, possibly, at  $  x _ {0} $
 +
itself where it is continuous, and if the derivative  $  f ^ { \prime } $
 +
is of constant sign on each side of  $  x _ {0} $
 +
in this neighbourhood, then for  $  x _ {0} $
 +
to be a strict local maximum (local minimum) point it is necessary and sufficient that the derivative changes sign from plus to minus, that is,  $  f ^ { \prime } ( x) > 0 $
 +
for  $  x < x _ {0} $
 +
and  $  f ^ { \prime } ( x) < 0 $
 +
for  $  x > x _ {0} $(
 +
respectively, from minus to plus;  $  f ^ { \prime } ( x) < 0 $
 +
for  $  x < x _ {0} $
 +
and  $  f ^ { \prime } ( x) > 0 $
 +
for  $  x > x _ {0} $).
 +
However, it is not possible to speak of the change of sign of the derivative at  $  x _ {0} $
 +
for every function  $  f $
 +
that is differentiable in a neighbourhood of  $  x _ {0} $.
 +
 
 +
If  $  f $
 +
has  $  m $
 +
derivatives at  $  x _ {0} $
 +
and if  $  f ^ { ( k) } ( x _ {0} ) = 0 $,
 +
$  k = 1 \dots m - 1 $,
 +
$  f ^ { ( m) } ( x _ {0} ) \neq 0 $,
 +
then for  $  x _ {0} $
 +
to be a strict local maximum point it is necessary and sufficient that  $  m $
 +
be even and that  $  f ^ { ( m) } ( x _ {0} ) < 0 $,
 +
and for a local minimum that  $  m $
 +
be even and  $  f ^ { ( m) } ( x _ {0} ) > 0 $.
 +
 
 +
Let  $  f ( x _ {1} \dots x _ {n} ) $
 +
be defined in an $  n $-
 +
dimensional neighbourhood of a point $  x  ^ {(} 0) = ( x _ {1}  ^ {(} 0) \dots x _ {n}  ^ {(} 0) ) $
 +
and let it be differentiable at this point. If $  x  ^ {(} 0) $
 +
is a non-strict local maximum (minimum) point, then the differential of $  f $
 +
at this point is equal to zero. This condition is equivalent to all first-order partial derivatives of $  f $
 +
being zero at this point. If the function has continuous second-order partial derivatives at $  x  ^ {(} 0) $,  
 +
if all its first-order derivatives are equal to zero at $  x  ^ {(} 0) $,  
 +
and if the second-order differential at $  x  ^ {(} 0) $
 +
is a negative-definite (positive-definite) quadratic form, then $  x  ^ {(} 0) $
 +
is a strict local maximum (minimum) point. Conditions for maximum and minimum points of differentiable functions are known when restrictions are imposed on the variation of the arguments in the domain: coupling equations must be satisfied. Necessary and sufficient conditions for a maximum (minimum) of a real-valued function with a more complicated structure of its domain of definition have been obtained in special areas of mathematics; for example, in [[Convex analysis|convex analysis]] and [[Mathematical programming|mathematical programming]] (see also [[Maximization and minimization of functions|Maximization and minimization of functions]]). Maximum and minimum points of functions on manifolds are studied in [[Variational calculus in the large|variational calculus in the large]], and maximum and minimum points for functions on function spaces, that is, for functionals, are studied in [[Variational calculus|variational calculus]]. There are also various numerical approximation methods for finding maximum and minimum points.
  
 
====References====
 
====References====
 
<table><TR><TD valign="top">[1]</TD> <TD valign="top">  V.A. Il'in,  E.G. Poznyak,  "Fundamentals of mathematical analysis" , '''1''' , MIR  (1982)  (Translated from Russian)</TD></TR><TR><TD valign="top">[2]</TD> <TD valign="top">  L.D. Kudryavtsev,  "A course in mathematical analysis" , '''1–2''' , Moscow  (1981)  (In Russian)</TD></TR><TR><TD valign="top">[3]</TD> <TD valign="top">  S.M. Nikol'skii,  "A course of mathematical analysis" , '''1''' , MIR  (1977)  (Translated from Russian)</TD></TR><TR><TD valign="top">[4]</TD> <TD valign="top">  N.S. Bakhvalov,  "Numerical methods: analysis, algebra, ordinary differential equations" , MIR  (1977)  (Translated from Russian)</TD></TR></table>
 
<table><TR><TD valign="top">[1]</TD> <TD valign="top">  V.A. Il'in,  E.G. Poznyak,  "Fundamentals of mathematical analysis" , '''1''' , MIR  (1982)  (Translated from Russian)</TD></TR><TR><TD valign="top">[2]</TD> <TD valign="top">  L.D. Kudryavtsev,  "A course in mathematical analysis" , '''1–2''' , Moscow  (1981)  (In Russian)</TD></TR><TR><TD valign="top">[3]</TD> <TD valign="top">  S.M. Nikol'skii,  "A course of mathematical analysis" , '''1''' , MIR  (1977)  (Translated from Russian)</TD></TR><TR><TD valign="top">[4]</TD> <TD valign="top">  N.S. Bakhvalov,  "Numerical methods: analysis, algebra, ordinary differential equations" , MIR  (1977)  (Translated from Russian)</TD></TR></table>
 
 
  
 
====Comments====
 
====Comments====
 
  
 
====References====
 
====References====
 
<table><TR><TD valign="top">[a1]</TD> <TD valign="top">  K.R. Stromberg,  "Introduction to classical real analysis" , Wadsworth  (1981)</TD></TR></table>
 
<table><TR><TD valign="top">[a1]</TD> <TD valign="top">  K.R. Stromberg,  "Introduction to classical real analysis" , Wadsworth  (1981)</TD></TR></table>

Latest revision as of 08:00, 6 June 2020


Points in the domain of definition of a real-valued function at which it takes its greatest and smallest values; such points are also called absolute maximum and absolute minimum points. If $ f $ is defined on a topological space $ X $, then a point $ x _ {0} $ is called a local maximum (local minimum) point if there is a neighbourhood $ U \subseteq X $ of $ x _ {0} $ such that $ x _ {0} $ is an absolute maximum (minimum) point for the restriction of $ f $ to this neighbourhood. One distinguishes between strict and non-strict maximum (minimum) points (both absolute and local). For example, a point $ x _ {0} \in \mathbf R $ is called a non-strict (strict) local maximum point of $ f $ if there is a neighbourhood $ U $ of $ x _ {0} $ such that for all $ x \in U $, $ f ( x) \leq f ( x _ {0} ) $( $ f( x) < f ( x _ {0} ) $, $ x \neq x _ {0} $).

For functions defined on finite-dimensional domains there are conditions and tests, in terms of differential calculus, for a given point to be a local maximum (minimum) point. Let $ f $ be defined in a neighbourhood of a point $ x _ {0} $ of the real line. If $ x _ {0} $ is a non-strict local maximum (minimum) point and if the derivative $ f ^ { \prime } ( x _ {0} ) $ exists, then the latter is equal to zero.

If a function $ f $ is differentiable in a neighbourhood of $ x _ {0} $ except, possibly, at $ x _ {0} $ itself where it is continuous, and if the derivative $ f ^ { \prime } $ is of constant sign on each side of $ x _ {0} $ in this neighbourhood, then for $ x _ {0} $ to be a strict local maximum (local minimum) point it is necessary and sufficient that the derivative changes sign from plus to minus, that is, $ f ^ { \prime } ( x) > 0 $ for $ x < x _ {0} $ and $ f ^ { \prime } ( x) < 0 $ for $ x > x _ {0} $( respectively, from minus to plus; $ f ^ { \prime } ( x) < 0 $ for $ x < x _ {0} $ and $ f ^ { \prime } ( x) > 0 $ for $ x > x _ {0} $). However, it is not possible to speak of the change of sign of the derivative at $ x _ {0} $ for every function $ f $ that is differentiable in a neighbourhood of $ x _ {0} $.

If $ f $ has $ m $ derivatives at $ x _ {0} $ and if $ f ^ { ( k) } ( x _ {0} ) = 0 $, $ k = 1 \dots m - 1 $, $ f ^ { ( m) } ( x _ {0} ) \neq 0 $, then for $ x _ {0} $ to be a strict local maximum point it is necessary and sufficient that $ m $ be even and that $ f ^ { ( m) } ( x _ {0} ) < 0 $, and for a local minimum that $ m $ be even and $ f ^ { ( m) } ( x _ {0} ) > 0 $.

Let $ f ( x _ {1} \dots x _ {n} ) $ be defined in an $ n $- dimensional neighbourhood of a point $ x ^ {(} 0) = ( x _ {1} ^ {(} 0) \dots x _ {n} ^ {(} 0) ) $ and let it be differentiable at this point. If $ x ^ {(} 0) $ is a non-strict local maximum (minimum) point, then the differential of $ f $ at this point is equal to zero. This condition is equivalent to all first-order partial derivatives of $ f $ being zero at this point. If the function has continuous second-order partial derivatives at $ x ^ {(} 0) $, if all its first-order derivatives are equal to zero at $ x ^ {(} 0) $, and if the second-order differential at $ x ^ {(} 0) $ is a negative-definite (positive-definite) quadratic form, then $ x ^ {(} 0) $ is a strict local maximum (minimum) point. Conditions for maximum and minimum points of differentiable functions are known when restrictions are imposed on the variation of the arguments in the domain: coupling equations must be satisfied. Necessary and sufficient conditions for a maximum (minimum) of a real-valued function with a more complicated structure of its domain of definition have been obtained in special areas of mathematics; for example, in convex analysis and mathematical programming (see also Maximization and minimization of functions). Maximum and minimum points of functions on manifolds are studied in variational calculus in the large, and maximum and minimum points for functions on function spaces, that is, for functionals, are studied in variational calculus. There are also various numerical approximation methods for finding maximum and minimum points.

References

[1] V.A. Il'in, E.G. Poznyak, "Fundamentals of mathematical analysis" , 1 , MIR (1982) (Translated from Russian)
[2] L.D. Kudryavtsev, "A course in mathematical analysis" , 1–2 , Moscow (1981) (In Russian)
[3] S.M. Nikol'skii, "A course of mathematical analysis" , 1 , MIR (1977) (Translated from Russian)
[4] N.S. Bakhvalov, "Numerical methods: analysis, algebra, ordinary differential equations" , MIR (1977) (Translated from Russian)

Comments

References

[a1] K.R. Stromberg, "Introduction to classical real analysis" , Wadsworth (1981)
How to Cite This Entry:
Maximum and minimum points. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Maximum_and_minimum_points&oldid=14508
This article was adapted from an original article by L.D. Kudryavtsev (originator), which appeared in Encyclopedia of Mathematics - ISBN 1402006098. See original article