Q_constraint: Quadratic Constraints
In ROI: R Optimization Infrastructure

Description Usage Arguments Value Author(s)

Quadratic constraints are typically of the form

\frac{1}{2}x^{\top}Q_ix + L_i x ≤q 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.

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, ...)

`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.