Currently I am working on an implementation of Benders Decomposition that solves a stochastic vehicle routing problem with synchronisation constraints.
Sadly, at the moment it is not performing fast enough to be a serviceable solution method.
The main problem I think is, that in the first stage of the stochastic problem, we basically generate 99% of the time tours that are rendered infeasible by the subproblem because all the information on time windows and the needed synchronisation is part of the subproblem.
So the number of feasibility cuts is extremely high.
In order to fix this, I tried to add a subset of the scenarios to the master problem, meaning it gets extended with the complete set of constraints for this subset.
It accelerated the method a little, but not enough.
Do you have further recommendations how I could deal this with problem?