Empirical convergence speed of inclusion functions for facility location problems

One of the key points in interval global optimization is the selection of a suitable inclusion function which allows to solve the problem efficiently. Usually, the tighter the inclusions provided by the inclusion function, the better, because this will make the accelerating devices used in the algorithm more effective at discarding boxes. On the other hand, whereas more sophisticated inclusion functions may give tighter inclusions, they require more computational effort than others providing larger overestimations. In an earlier paper, the empirical convergence speed of inclusion functions was defined and studied, and it was shown to be a good indicator of the inclusion precision. If the empirical convergence speed is analyzed for a given type of functions, then one can select the appropriate inclusion function to be used when dealing with those type of functions. In this paper we present such a study, dealing with functions used in competitive facility location problems.