Reference

qp = QuadraticModel(c, Hrows, Hcols, Hvals; Arows = Arows, Acols = Acols, Avals = Avals, 
                    lcon = lcon, ucon = ucon, lvar = lvar, uvar = uvar)

qp = QuadraticModel(c, H; A = A, lcon = lcon, ucon = ucon, lvar = lvar, uvar = uvar)

Create a Quadratic model $min ~\tfrac{1}{2} x^T Q x + c^T x + c_0$ with optional bounds lvar ≦ x ≦ uvar and optional linear constraints lcon ≦ Ax ≦ ucon.

You can also use QPSReader.jl to create a Quadratic model from a QPS file:

using QPSReader
qps = readqps("QAFIRO.SIF")
qp = QuadraticModel(qps)

QuadraticModel(nlp, x)

Creates a quadratic Taylor model of nlp around x.

postsolve!(qm::QuadraticModel{T, S}, psqm::PresolvedQuadraticModel{T, S}, 
           x_in::S, x_out::S) where {T, S}

Retrieve the solution x_out of the original QP qm given the solution of the presolved QP (psqm) x_in.

psqm = presolve(qm::QuadraticModel{T, S}; kwargs...)

Apply a presolve routine to qm and returns a PresolvedQuadraticModel{T, S} <: AbstractQuadraticModel{T, S}. The presolve operations currently implemented are:

• remove_ifix!

xrm, c0ps, nvarrm = remove_ifix!(ifix, Hrows, Hcols, Hvals, nvar, 
                                 Arows, Acols, Avals, c, c0, 
                                 lvar, uvar, lcon, ucon)

Remove rows and columns in H, columns in A, and elements in lcon and ucon corresponding to fixed variables, that are in ifix (They should be the indices i where lvar[i] == uvar[i]).

Returns the removed elements of lvar (or uvar), the constant term in the QP objective c0ps resulting from the fixed variables, and the new number of variables nvarrm. Hrows, Hcols, Hvals, Arows, Acols, Avals, c, lvar, uvar, lcon and ucon are updated in-place.