Cool post. Some insight into why this problem is so hard: what this post is describing seems to be an integer linear programming problem [1]. I.e. optimizing a linear cost function constrained by (convex) linear bounds with integer-valued variables. The reason it's so difficult is that ILP is an NP-hard problem. Finding the right way to represent program source is also tricky, but, as the post says, doing so in a way that caters to the extremely performance-sensitive solver code is the really difficult bit. A better approach might be to produce an explicit ILP program and use an ILP solver to decide where the line breaks should go. As with many NP-hard problems (e.g. SAT, TSP), there are very good solvers these days that are much faster than anything you could ever hope to write yourself – and they produce fully optimal solutions.

[1] https://en.wikipedia.org/wiki/Integer_programming