* When using the constraint from _Thinning out Steiner trees: a node-based model for uniform edge costs_ it takes ~5 s.
* As this constraint is not applyable I added another constraint which is "inspired" by the previous constraint. After implementing this constraint solving the bigger-leaf with k = 2 took ~80s.
* Then I tried to add vertex separator constraints before starting the optimization process to see in what manner the runtime is affected.
-- Actually the runtime is reduced by this approach in a significant amount. And as more constraints you add the faster the problem is solved.
-- I used constraints where I assumed that they would be added anyway in the iteration process. (separators which separate sets of vertices and the root)
-- One thing which could be observed was that the runtime shows a correlation between the number of constraints which still had to be added in the iteration process and the runtime.
-- But the ASP version was still a lot faster.
- Actually the runtime is reduced by this approach in a significant amount. And as more constraints you add the faster the problem is solved.
- I used constraints where I assumed that they would be added anyway in the iteration process. (separators which separate sets of vertices and the root)
- One thing which could be observed was that the runtime shows a correlation between the number of constraints which still had to be added in the iteration process and the runtime.
- But the ASP version was still a lot faster.
* I also implemented another type of inequalities to induce connectivity. Unfortunately this type of inequalites does not induce connectivity on graphs that are not acyclic. So they can not be used without the other inequalities. When used together the runtime is not reduced.
* I documented my observations via screenshots and wrote them into a table.
