The leader opens p facilities, anticipating that the follower will react to
the decision by opening his own r facilities. The decision makers try to
maximize their own profits. This Stackelberg game is ΣP
2 -hard. So, we
develop a hybrid memetic algorithm for it. A probabilistic tabu search
heuristic is applied for improving the offsprings. To obtain an upper
bound, we reformulate the problem as a mixed integer program with an
exponential number of constraints and variables. Selecting some of them,
we get the desired upper bound. To find optimal solutions, we iteratively
modify the subset of the constraints and variables. This approach is
tested on the benchmarks from the library Discrete Location Problems.
The optimal solutions are found for r = p = 5, 100 clients, and 100
facilities.