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clearly separate creation of the optimization problem

This commit is contained in:
kalmarek 2018-08-20 03:46:44 +02:00
parent d2f6682a39
commit 13bc1bef8b

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@ -31,27 +31,25 @@ function spLaplacian(RG::GroupRing{R}, S, T::Type=Float64) where {R<:Ring}
return result
end
function create_SDP_problem(Δ::GroupRingElem, matrix_constraints; upper_bound=Inf)
N = size(parent(Δ).pm, 1)
Δ² = Δ*Δ
@assert length(Δ.coeffs) == length(matrix_constraints)
function SOS_problem(X::GroupRingElem, orderunit::GroupRingElem; upper_bound=Inf)
N = size(parent(X).pm, 1)
matrix_constraints = PropertyT.constraints(parent(X).pm)
m = JuMP.Model();
JuMP.@variable(m, P[1:N, 1:N])
JuMP.@SDconstraint(m, P >= 0)
JuMP.@constraint(m, sum(P[i] for i in eachindex(P)) == 0)
JuMP.@variable(m, λ)
if upper_bound < Inf
JuMP.@variable(m, 0.0 <= λ <= upper_bound)
else
JuMP.@variable(m, λ >= 0)
JuMP.@constraint(m, λ <= upper_bound)
end
for (pairs, δ², δ) in zip(matrix_constraints, Δ².coeffs, Δ.coeffs)
JuMP.@constraint(m, sum(P[i,j] for (i,j) in pairs) == δ² - λ*δ)
for (cnstr, x, u) in zip(matrix_constraints, X.coeffs, orderunit.coeffs)
JuMP.@constraint(m, sum(P[cnstr]) == x - λ*u)
end
JuMP.@objective(m, Max, λ)
return m, λ, P
end