To complete @dpo’s answer and to conform with the notations of Reference · QuadraticModels.jl , I think your problem can be written as
\min_x \tfrac{1}{2}x^THx \quad \text{s.t.} \quad Ax = b, \quad \text{and} \quad x_i \ge 0, \quad i=1, ..., n,
where
x = \begin{bmatrix} f \\ r \end{bmatrix}, H = \begin{bmatrix} 2 \alpha I & 0 \\ 0 & I \end{bmatrix}, A = \begin{bmatrix} K & I \end{bmatrix}, b = g, and f \in \mathbb{R}^n
Then, a small example with RipQP.jl would give
using RipQP, QuadraticModels, LinearAlgebra, SparseArrays
m, n = 30, 100
K = rand(m, n)
α = 1.0
g = rand(m)
A = [sparse(K) I]
H = [2*α*I spzeros(n, m);
spzeros(m, n) 2*I]
c = zeros(m + n)
lvar = [zeros(n); fill(-Inf, m)]
qm = QuadraticModel(c, H; A = A, lcon = g, ucon = g, lvar = lvar)
stats = ripqp(qm)
f, r = stats.solution[1:n], stats.solution[n+1:n+m]