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xy or VectorLessEqual [{x,y}]

yields True for vectors of length n if xiyi for all components .

xκy or VectorLessEqual [{x,y},κ]

yields True for x and y if y-xκ, where κ is a proper convex cone.

Details
Details and Options Details and Options
Examples  
Basic Examples  
Scope  
Applications  
Basic Applications  
Optimization over Vector Inequalities  
Solving Vector Inequalities  
Integration over Vector Inequality Regions  
Matrix Inequalities  
Properties & Relations  
Possible Issues  
See Also
Related Guides
History
Cite this Page

xy or VectorLessEqual [{x,y}]

yields True for vectors of length n if xiyi for all components .

xκy or VectorLessEqual [{x,y},κ]

yields True for x and y if y-xκ, where κ is a proper convex cone.

Details

  • VectorLessEqual gives a partial ordering of vectors, matrices and arrays that is compatible with vector space operations, so that and imply for all .
  • VectorLessEqual is typically used to specify vector inequalities for constrained optimization, inequality solving and integration. It is also used to define minimal elements in vector optimization.
  • When x and y are -vectors, xy is equivalent to . That is, each part of x is less than or equal to the corresponding part of y for the relation to be true.
  • When x and y are dimension arrays, xy is equivalent to . That is, each part of x is less than or equal to the corresponding part of y for the relation to be true.
  • xy remains unevaluated if x or y has non-numeric elements; typically gives True or False otherwise.
  • When x is an n-vector and y is a numeric scalar, xy yields True if xiy for all components .
  • By using the character , entered as v<= or \[VectorLessEqual] , with subscripts vector inequalities can be entered as follows:
  • xy VectorLessEqual[{x,y}] the standard vector inequality
    x_(kappa)y VectorLessEqual[{x,y},κ] vector inequality defined by a cone κ
  • In general, one can use a proper convex cone κ to specify a vector inequality. The set is the same as κ.
  • Possible cone specifications κ in for vectors x include:
  • {"NonNegativeCone", n} TemplateBox[{n}, NonNegativeConeList] such that
    {"NormCone", n} TemplateBox[{n}, NormConeList] such that Norm [{x1,,xn-1}]xn
    "ExponentialCone" TemplateBox[{}, ExponentialConeString] such that
    "DualExponentialCone" TemplateBox[{}, DualExponentialConeString] such that or
    {"PowerCone",α} TemplateBox[{alpha}, PowerConeList] such that
    {"DualPowerCone",α} TemplateBox[{alpha}, DualPowerConeList] such that
  • Possible cone specifications κ in for matrices x include:
  • "NonNegativeCone" TemplateBox[{}, NonNegativeConeString] such that
    {"SemidefiniteCone", n} TemplateBox[{n}, SemidefiniteConeList] symmetric positive semidefinite matrices
  • Possible cone specifications κ in for arrays x include:
  • "NonNegativeCone" TemplateBox[{}, NonNegativeConeString] such that
  • For exact numeric quantities, VectorLessEqual internally uses numerical approximations to establish numerical ordering. This process can be affected by the setting of the global variable $MaxExtraPrecision .

Examples

open all close all

Basic Examples  (3)

xy yields True when xiyi is True for all i=1,,n:

xy yields False when xi>yi is False for any i=1,,n:

Represent a vector inequality:

When v is replaced by numerical vector space elements, the inequality gives True or False :

The cone is also given by :

The cone is also given by :

The cuboid is also given by :

Scope  (7)

Determine if all of the elements in a vector are non-negative:

Determine if all components are less than or equal to 1:

!xy does not imply xy:

For each component, !xiyi does imply xi>yi:

Compare the components of two matrices:

Compare symmetric matrices:

Represent the condition that Norm [{x,y}]<=1:

Represent the condition that :

Show where for non-negative x,y with α between 0 and 1:

Applications  (8)

Basic Applications  (1)

VectorLessEqual is a fast way to compare many elements:

Optimization over Vector Inequalities  (1)

Solving Vector Inequalities  (1)

The inequality represents the cuboid Cuboid [pmin,pmax]:

Integration over Vector Inequality Regions  (2)

Integrate over the non-negative quadrant :

Using vector variables:

Integrate over the non-negative orthant:

Integrate over the rectangle :

Using vector variables:

Integrate over the cuboid :

Matrix Inequalities  (3)

Use the standard vector order to represent the set of non-negative matrices:

Give the set of interval bounded matrices:

Use the semidefinite cone to define the set of symmetric positive semidefinite matrices:

Define the set of symmetric matrices with smallest eigenvalue and largest eigenvalue by using , where n=IdentityMatrix [n] and κ="SemidefiniteCone". This finds the set of symmetric matrices with eigenvalues between 1 and 2, i.e. :

Formulate the same problem using matrix variables:

Find an instance of such a matrix:

Check the result:

Properties & Relations  (3)

VectorLessEqual is compatible with a vector space operation:

Adding vectors to both sides for any vector :

Multiplying by positive constants for any :

xy is a (non-strict) partial order, i.e. reflexive, antisymmetric and transitive:

Reflexive, i.e. for all elements :

Antisymmetric, i.e. if and then :

Transitive, i.e. if and then :

xκy are partial orders but not total orders, so there are incomparable elements:

Neither nor is true, because and are incomparable elements:

The set of vectors and . These are the comparable elements to :

Possible Issues  (1)

Vector orders are partial orders, so the negation of is not equivalent to :

Here both and are false:

Visualize and . The difference of these sets consists of incomparable elements:

Wolfram Research (2019), VectorLessEqual, Wolfram Language function, https://reference.wolfram.com/language/ref/VectorLessEqual.html.

Text

Wolfram Research (2019), VectorLessEqual, Wolfram Language function, https://reference.wolfram.com/language/ref/VectorLessEqual.html.

CMS

Wolfram Language. 2019. "VectorLessEqual." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/VectorLessEqual.html.

APA

Wolfram Language. (2019). VectorLessEqual. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/VectorLessEqual.html

BibTeX

@misc{reference.wolfram_2025_vectorlessequal, author="Wolfram Research", title="{VectorLessEqual}", year="2019", howpublished="\url{https://reference.wolfram.com/language/ref/VectorLessEqual.html}", note=[Accessed: 24-November-2025]}

BibLaTeX

@online{reference.wolfram_2025_vectorlessequal, organization={Wolfram Research}, title={VectorLessEqual}, year={2019}, url={https://reference.wolfram.com/language/ref/VectorLessEqual.html}, note=[Accessed: 24-November-2025]}

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