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:
-
xy VectorLessEqual[{x,y}] the standard vector inequalityx_(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"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 allBasic Examples (3)
xy yields True when xi≤yi 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, !xi≤yi 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 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:
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:
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: 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]}