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Support quadratic constraints in MathOptNLSModel
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@amontoison
amontoison committed Jun 20, 2024
1 parent a41e7d3 commit 24709d4
Showing 1 changed file with 122 additions and 25 deletions.
147 changes: 122 additions & 25 deletions src/moi_nls_model.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@ mutable struct MathOptNLSModel <: AbstractNLSModel{Float64, Vector{Float64}}
linequ::LinearEquations
nlequ::NonLinearStructure
lincon::LinearConstraints
quadcon::QuadraticConstraints
nlcon::NonLinearStructure
counters::NLSCounters
end
Expand Down Expand Up @@ -39,11 +40,11 @@ function MathOptNLSModel(cmodel::JuMP.Model, F; hessian::Bool = true, name::Stri
Fnnzj = linequ.nnzj + nlequ.nnzj
Fnnzh = nlequ.nnzh

ncon = nlin + nnln
lcon = vcat(lin_lcon, nl_lcon)
ucon = vcat(lin_ucon, nl_ucon)
cnnzj = lincon.nnzj + nlcon.nnzj
cnnzh = lls.nnzh + nlcon.nnzh
ncon = nlin + quadcon.nquad + nnln
lcon = vcat(lin_lcon, quad_lcon, nl_lcon)
ucon = vcat(lin_ucon, quad_ucon, nl_ucon)
cnnzj = lincon.nnzj + quadcon.nnzj + nlcon.nnzj
cnnzh = lls.nnzh + quadcon.nnzh + nlcon.nnzh

meta = NLPModelMeta(
nvar,
Expand All @@ -58,7 +59,7 @@ function MathOptNLSModel(cmodel::JuMP.Model, F; hessian::Bool = true, name::Stri
nnzh = cnnzh,
lin = collect(1:nlin),
lin_nnzj = lincon.nnzj,
nln_nnzj = nlcon.nnzj,
nln_nnzj = quadcon.nnzj + nlcon.nnzj,
minimize = objective_sense(cmodel) == MOI.MIN_SENSE,
islp = false,
name = name,
Expand All @@ -73,6 +74,7 @@ function MathOptNLSModel(cmodel::JuMP.Model, F; hessian::Bool = true, name::Stri
linequ,
nlequ,
lincon,
quadcon,
nlcon,
NLSCounters(),
)
Expand Down Expand Up @@ -253,7 +255,13 @@ end

function NLPModels.cons_nln!(nls::MathOptNLSModel, x::AbstractVector, c::AbstractVector)
increment!(nls, :neval_cons_nln)
MOI.eval_constraint(nls.ceval, c, x)
for i = 1:(nls.quadcon.nquad)
qcon = nls.quadcon.constraints[i]
c[i] = 0.5 * coo_sym_dot(qcon.A.rows, qcon.A.cols, qcon.A.vals, x, x) + dot(qcon.b, x)
end
if nls.meta.nnln > nls.quadcon.nquad
MOI.eval_constraint(nls.ceval, view(c, (nls.quadcon.nquad + 1):(nls.meta.nnln)), x)
end
return c
end

Expand All @@ -272,8 +280,20 @@ function NLPModels.jac_nln_structure!(
rows::AbstractVector{<:Integer},
cols::AbstractVector{<:Integer},
)
view(rows, 1:(nls.nlcon.nnzj)) .= nls.nlcon.jac_rows
view(cols, 1:(nls.nlcon.nnzj)) .= nls.nlcon.jac_cols
if nls.quadcon.nquad > 0
index = 0
for i = 1:(nls.quadcon.nquad)
qcon = nls.quadcon.constraints[i]
view(rows, index+1:index+qcon.nnzg) .= i
view(cols, index+1:index+qcon.nnzg) .= qcon.g
index += qcon.nnzg
end
end
if nls.meta.nnln > nls.quadcon.nquad
ind_nnln = (nls.quadcon.nnzj + 1):(nls.quadcon.nnzj + nls.nlcon.nnzj)
view(rows, ind_nnln) .= nls.nlcon.jac_rows
view(cols, ind_nnln) .= nls.nlcon.jac_cols
end
return rows, cols
end

Expand All @@ -285,7 +305,33 @@ end

function NLPModels.jac_nln_coord!(nls::MathOptNLSModel, x::AbstractVector, vals::AbstractVector)
increment!(nls, :neval_jac_nln)
MOI.eval_constraint_jacobian(nls.ceval, view(vals, 1:(nls.nlcon.nnzj)), x)
if nls.quadcon.nquad > 0
index = 0
view(vals, 1:nls.quadcon.nnzj) .= 0.0
for i = 1:(nls.quadcon.nquad)
qcon = nls.quadcon.constraints[i]
for (j, ind) in enumerate(qcon.b.nzind)
k = qcon.dg[ind]
vals[index+k] += qcon.b.nzval[j]
end
for j = 1:qcon.nnzh
row = qcon.A.rows[j]
col = qcon.A.cols[j]
val = qcon.A.vals[j]
k1 = qcon.dg[row]
vals[index+k1] += val * x[col]
if row != col
k2 = qcon.dg[col]
vals[index+k2] += val * x[row]
end
end
index += qcon.nnzg
end
end
if nls.meta.nnln > nls.quadcon.nquad
ind_nnln = (nls.quadcon.nnzj + 1):(nls.quadcon.nnzj + nls.nlcon.nnzj)
MOI.eval_constraint_jacobian(nls.ceval, view(vals, ind_nnln), x)
end
return vals
end

Expand Down Expand Up @@ -313,7 +359,18 @@ function NLPModels.jprod_nln!(
Jv::AbstractVector,
)
increment!(nls, :neval_jprod_nln)
MOI.eval_constraint_jacobian_product(nls.ceval, Jv, x, v)
if nls.meta.nnln > nls.quadcon.nquad
ind_nnln = (nls.quadcon.nquad + 1):(nls.meta.nnln)
MOI.eval_constraint_jacobian_product(nls.ceval, view(Jv, ind_nnln), x, v)
end
(nls.meta.nnln == nls.quadcon.nquad) && (Jv .= 0.0)
if nls.quadcon.nquad > 0
for i = 1:(nls.quadcon.nquad)
# Jv[i] = (Aᵢ * x + bᵢ)ᵀ * v
qcon = nls.quadcon.constraints[i]
v[i] += coo_sym_dot(qcon.A.rows, qcon.A.cols, qcon.A.vals, x, v) + dot(qcon.b, v)
end
end
return Jv
end

Expand Down Expand Up @@ -341,7 +398,19 @@ function NLPModels.jtprod_nln!(
Jtv::AbstractVector,
)
increment!(nls, :neval_jtprod_nln)
MOI.eval_constraint_jacobian_transpose_product(nls.ceval, Jtv, x, v)
if nls.meta.nnln > nls.quadcon.nquad
ind_nnln = (nls.quadcon.nquad + 1):(nls.meta.nnln)
MOI.eval_constraint_jacobian_transpose_product(nls.ceval, Jtv, x, view(v, ind_nnln))
end
(nls.meta.nnln == nls.quadcon.nquad) && (Jtv .= 0.0)
if nls.quadcon.nquad > 0
for i = 1:(nls.quadcon.nquad)
# Jtv += v[i] * (Aᵢ * x + bᵢ)
qcon = nls.quadcon.constraints[i]
coo_sym_add_mul!(rows, cols, vals, x, Jtv, v[i])
Jtv .+= v[i] .* qcon.b
end
end
return Jtv
end

Expand All @@ -354,9 +423,18 @@ function NLPModels.hess_structure!(
view(rows, 1:(nls.lls.nnzh)) .= nls.lls.hessian.rows
view(cols, 1:(nls.lls.nnzh)) .= nls.lls.hessian.cols
end
if nls.nls_meta.nnln > 0
view(rows, (nls.lls.nnzh + 1):(nls.meta.nnzh)) .= nls.nlcon.hess_rows
view(cols, (nls.lls.nnzh + 1):(nls.meta.nnzh)) .= nls.nlcon.hess_cols
if (nls.nls_meta.nnln > 0) || (nlp.meta.nnln > nlp.quadcon.nquad)
view(rows, (nls.lls.nnzh + nlp.quadcon.nnzh + 1):(nls.meta.nnzh)) .= nls.nlcon.hess_rows
view(cols, (nls.lls.nnzh + nlp.quadcon.nnzh + 1):(nls.meta.nnzh)) .= nls.nlcon.hess_cols
end
if nls.quadcon.nquad > 0
index = nls.lls.nnzh
for i = 1:(nls.quadcon.nquad)
qcon = nls.quadcon.constraints[i]
view(rows, (index + 1):(index + qcon.nnzh)) .= qcon.A.rows
view(cols, (index + 1):(index + qcon.nnzh)) .= qcon.A.cols
index += qcon.nnzh
end
end
return rows, cols
end
Expand All @@ -372,15 +450,24 @@ function NLPModels.hess_coord!(
if nls.nls_meta.nlin > 0
view(vals, 1:(nls.lls.nnzh)) .= obj_weight .* nls.lls.hessian.vals
end
if (nls.nls_meta.nnln > 0) || (nls.meta.nnln > 0)
if (nls.nls_meta.nnln > 0) || (nls.meta.nnln > nls.quadcon.nquad)
λ = view(y, (nls.meta.nlin + nls.quadcon.nquad + 1):(nls.meta.ncon))
MOI.eval_hessian_lagrangian(
nls.ceval,
view(vals, (nls.lls.nnzh + 1):(nls.meta.nnzh)),
view(vals, (nls.lls.nnzh + nls.quadcon.nnzh + 1):(nls.meta.nnzh)),
x,
obj_weight,
view(y, nls.meta.nln),
λ
)
end
if nls.quadcon.nquad > 0
index = nls.lls.nnzh
for i = 1:(nls.quadcon.nquad)
qcon = nls.quadcon.constraints[i]
view(vals, (index + 1):(index + qcon.nnzh)) .= y[i] .* qcon.A.vals
index += qcon.nnzh
end
end
return vals
end

Expand All @@ -394,16 +481,18 @@ function NLPModels.hess_coord!(
if nls.nls_meta.nlin > 0
view(vals, 1:(nls.lls.nnzh)) .= obj_weight .* nls.lls.hessian.vals
end
view(vals, (nls.lls.nnzh + 1):(nls.lls.nnzh + nls.quadcon.nnzh)) .= 0.0
if nls.nls_meta.nnln > 0
λ = zeros(nlp.meta.nnln - nlp.quadcon.nquad) # Should be stored in the structure MathOptNLSModel
MOI.eval_hessian_lagrangian(
nls.ceval,
view(vals, (nls.lls.nnzh + 1):(nls.meta.nnzh)),
view(vals, (nls.lls.nnzh + nls.quadcon.nnzh + 1):(nls.meta.nnzh)),
x,
obj_weight,
zeros(nls.meta.nnln),
λ,
)
else
view(vals, (nls.lls.nnzh + 1):(nls.meta.nnzh)) .= 0.0
view(vals, (nls.lls.nnzh + nls.quadcon.nnzh + 1):(nls.meta.nnzh)) .= 0.0
end
return vals
end
Expand All @@ -417,11 +506,12 @@ function NLPModels.hprod!(
obj_weight::Float64 = 1.0,
)
increment!(nls, :neval_hprod)
if (nls.nls_meta.nnln > 0) || (nls.meta.nnln > 0)
MOI.eval_hessian_lagrangian_product(nls.ceval, hv, x, v, obj_weight, view(y, nls.meta.nln))
if (nls.nls_meta.nnln > 0) || (nls.meta.nnln > nls.quadcon.nquad)
λ = view(y, (nls.meta.nlin + nls.quadcon.nquad + 1):(nls.meta.ncon))
MOI.eval_hessian_lagrangian_product(nls.ceval, hv, x, v, obj_weight, λ)
end
(nls.nls_meta.nnln == 0) && (nls.meta.nnln == nls.quadcon.nquad) && (hv .= 0.0)
if nls.nls_meta.nlin > 0
(nls.nls_meta.nnln == 0) && (nls.meta.nnln == 0) && (hv .= 0.0)
coo_sym_add_mul!(
nls.lls.hessian.rows,
nls.lls.hessian.cols,
Expand All @@ -431,6 +521,12 @@ function NLPModels.hprod!(
obj_weight,
)
end
if nls.quadcon.nquad > 0
for i = 1:(nls.quadcon.nquad)
qcon = nls.quadcon.constraints[i]
coo_sym_add_mul!(qcon.A.rows, qcon.A.cols, qcon.A.vals, v, hv, y[nls.meta.nlin + i])
end
end
return hv
end

Expand All @@ -443,7 +539,8 @@ function NLPModels.hprod!(
)
increment!(nls, :neval_hprod)
if nls.nls_meta.nnln > 0
MOI.eval_hessian_lagrangian_product(nls.ceval, hv, x, v, obj_weight, zeros(nls.meta.nnln))
λ = zeros(nls.meta.nnln - nls.quadcon.nquad) # Should be stored in the structure MathOptNLSModel
MOI.eval_hessian_lagrangian_product(nls.ceval, hv, x, v, obj_weight, λ)
end
if nls.nls_meta.nlin > 0
(nls.nls_meta.nnln == 0) && (hv .= 0.0)
Expand Down

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