PROBABILISTIC, MAXIMAL COVERING LOCATION– ALLOCATION MODELS FOR CONGESTED SYSTEMS (original) (raw)

When dealing with the design of service networks, such as health and emergency medical services, banking or distributed ticket-selling services, the location of service centers has a strong influence on the congestion at each of them,and, consequently, on the quality of service. In this paper, several probabilistic maximal covering location– allocation models with constrainedwaiting time for queue length are presented to consider service congestion.The firstmodel considers the location of a given number of single-server centers such that the maximum population is served within a standard distance, and nobody stands in line for longer than a given time or with more than a predetermined number of other users. Several maximal coverage models are then formulated with one or more servers per service center.A new heuristic is developed to solve the models and tested in a 30-node network.