Hi everyone,
I am relatively new to CVXR and I am trying to model an optimization problem that involves both linear constraints and a norm-based objective. Specifically…, I want to minimize the L2 norm of a vector x, subject to a few linear inequality constraints like Ax ≤ b and an equality constraint like Cx = d.
I have read through some examples in the documentation…, but I am still unsure about the best way to properly set this up so that the DCP rules are satisfied. I am using CVXR in R and here’s a basic idea of my current approach:
x <- Variable(n)
objective <- Minimize(norm(x, 2))
constraints <- list(A %*% x <= b, C %*% x == d)
problem <- Problem(objective, constraints)
Does this look valid, or am I missing something subtle in how CVXR handles these norms and constraints together: ?? Any insights or corrections would be really appreciated !! I have also read this thread https://ask.cvxr.com/t/problem-in-formulating-my-problem-in-cvx-advanced-excel-course-in-kolkata but still need some more help.
Thanks in advance !!
Marcelo