Cross posted here, but asking a variant on this forum.
I want to write a sum of piecewise linear constraints as an LP and am hoping to compare my approach with how
JuMP does it.
In particular, I believe that I can express the following constraint:
where x,y are scalar decision variables, and c_i, d_i, e, f \geq 0 as the set of linear constraints
I tried looking at the actual constraints that
Convex.jl is using when it parses (*) by printing
problem.constraints, but but it doesn’t seem to show how it breaks down (*) into simpler constraints. Where in the source would I look, or is there a way to print off the simplified constraints (for either
Convex.jl) and see how the solvers are parsing them?