Q_constraint: Quadratic Constraints

In ROI: R Optimization Infrastructure

Quadratic Constraints

Description

Quadratic constraints are typically of the form

\frac{1}{2}x^{\top}Q_ix + L_i x \leq rhs_i

where Q_i is the ith of m (sparse) matrices (all of dimension n \times n) giving the coefficients of the quadratic part of the equation. The m \times n (sparse) matrix L holds the coefficients of the linear part of the equation and L_i refers to the ith row. The right hand side of the constraints is represented by the vector rhs.

Usage

Q_constraint(Q, L, dir, rhs, names = NULL)

## S3 method for class 'Q_constraint'
variable.names(object, ...)

as.Q_constraint(x)

is.Q_constraint(x)

## S3 method for class 'Q_constraint'
length(x)

## S3 method for class 'Q_constraint'
terms(x, ...)

Arguments

Q	a list of (sparse) matrices representing the quadratic part of each constraint.
L	a numeric vector of length n (a single constraint) or a matrix of dimension m \times n, where n is the number of objective variables and m is the number of constraints. Matrices can be of class "simple_triplet_matrix" to allow a sparse representation of constraints.
dir	a character vector with the directions of the constraints. Each element must be one of "<=", ">=" or "==".
rhs	a numeric vector with the right hand side of the constraints.
names	an optional character vector giving the names of x (row/column names of Q, column names of A).
object	an R object.
...	further arguments passed to or from other methods (currently ignored).
x	an R object.

Value

an object of class "Q_constraint" which inherits from "constraint".

Author(s)

Stefan Theussl

ROI documentation built on April 21, 2023, 1:11 a.m.