Spatial organization of public services: models and applications

Location decisions are crucial in the spatial organization in both public and private sectors as they can have a long term impact on operational performances and on service levels. Social cost minimization, universality of services and equity, expressed in terms of users' accessibility, are the main objectives in public services contexts. Nevertheless, the enduring trend of public expenditures revision poses, also in the public sectors, the need to pursue objectives of economic efficiency. In the literature, two families of optimization problems are typically used to address these problems, namely Facility Location Problems (FLPs) and Districting Problems (DPs). The aim of this thesis is to show how FLPs and DPs can be used to underpin spatial organization processes of public services, providing analytical models able to assist the decision making. To this end, novel mathematical models are developed with application to the healthcare and postal service sectors. In particular, a hierarchical facility location model is formulated to reorganize an existing regional Blood Management System (BMS) while an integrated location-districting model is proposed for the organization of postal collection operations in urban areas. A constructive heuristic procedure is also devised to solve the latter problem. Extensive computational experiments are realized to validate the proposed models and to show their capability to provide insightful managerial implications. Finally, the thesis aims at filling another existing gap in the literature due to the absence of stochastic models for DPs. Hence, a two-stage stochastic program for districting is introduced and tested on real georgaphic data. Several extensions of the proposed modeling framework are also discussed.