Improved local search for universal facility location

We consider the universal facility location problem in which the goal is to assign clients to facilities in order to minimize the sum of connection and facility costs. The connection cost is proportional to the distance each client has to travel to its assigned facility, whereas the cost of a facility is a non-decreasing function depending on the number of clients assigned to the facility. This model generalizes several variants of facility location problems. We present a (5.83 + epsilon) approximation algorithm for this problem based on local search technique.