xy or VectorLessEqual[{x,y}]
yields True for vectors of length n if xi≤yi for all components
.
xκy or VectorLessEqual[{x,y},κ]
yields True for x and y if y-x∈κ, where κ is a proper convex cone.
VectorLessEqual 
xy or VectorLessEqual[{x,y}]
yields True for vectors of length n if xi≤yi for all components
.
xκy or VectorLessEqual[{x,y},κ]
yields True for x and y if y-x∈κ, 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 xi≤y for all components
. - By using the character , entered as
v<=
or \[VectorLessEqual], with subscripts vector inequalities can be entered as follows: -

VectorLessEqual[{x,y}] the standard vector inequality 
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] TemplateBox[{n}, NonNegativeConeList]](Files/VectorLessEqual.en/21.png)
such that 
{"NormCone", n} ![TemplateBox[{n}, NormConeList] TemplateBox[{n}, NormConeList]](Files/VectorLessEqual.en/24.png)
such that Norm[{x1,…,xn-1}]≤xn"ExponentialCone" ![TemplateBox[{}, ExponentialConeString] TemplateBox[{}, ExponentialConeString]](Files/VectorLessEqual.en/26.png)
such that 
"DualExponentialCone" ![TemplateBox[{}, DualExponentialConeString] TemplateBox[{}, DualExponentialConeString]](Files/VectorLessEqual.en/29.png)
such that
or 
{"PowerCone",α} ![TemplateBox[{alpha}, PowerConeList] TemplateBox[{alpha}, PowerConeList]](Files/VectorLessEqual.en/33.png)
such that 
{"DualPowerCone",α} ![TemplateBox[{alpha}, DualPowerConeList] TemplateBox[{alpha}, DualPowerConeList]](Files/VectorLessEqual.en/36.png)
such that 
- Possible cone specifications κ in
for matrices x include: -
"NonNegativeCone" ![TemplateBox[{}, NonNegativeConeString] TemplateBox[{}, NonNegativeConeString]](Files/VectorLessEqual.en/40.png)
such that 
{"SemidefiniteCone", n} ![TemplateBox[{n}, SemidefiniteConeList] TemplateBox[{n}, SemidefiniteConeList]](Files/VectorLessEqual.en/43.png)
symmetric positive semidefinite matrices 
- Possible cone specifications κ in
for arrays x include: -
"NonNegativeCone" ![TemplateBox[{}, NonNegativeConeString] TemplateBox[{}, NonNegativeConeString]](Files/VectorLessEqual.en/46.png)
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 allBasic Examples (3)
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:
For each component, !xi≤yi does imply xi>yi:
Compare the components of two matrices:
Represent the condition that Norm[{x,y}]<=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)
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 ℐn=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:
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
:
Related Guides
History
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: 28-October-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: 28-October-2025]}