Department of Statistics and Operations Research,
University of Lisbon
Computers & Operations Research
Video recording: [Link]
Capturing Uncertainty in Districting Problems: Towards more comprehensive modeling frameworks
Districting Problems aim at partitioning a set of basic Territorial Units (TUs), into a set of larger clusters, called districts. This is done according to several planning criteria such as balancing, contiguity and compactness. These problems have a wide range of applications that include strategic service planning and management, school systems, energy and power distribution networks, design of police districts, waste collection, transportation, design of commercial areas to assign sales forces, and distribution logistics. In this seminar, a family of stochastic districting problems is discussed. Demand is assumed to be represented by a random vector with a given joint cumulative distribution function. A two-stage mixed-integer stochastic programming model is proposed. The first stage comprises the decision about the initial territory design. In the second stage, i.e., after demand becomes known, balancing requirements are to be met. This can be accomplished by means of different recourse actions such as outsourcing or reassignment of TUs. The objective function accounts for the total expected cost. A first model is introduced that is later extended to account for several aspects of practical relevance. Computational results were obtained for instances that make use of real geographical data. Those results as also reported in this presentation.
Francisco Saldanha da Gama is professor of Operations Research at the Department of Statistics and Operations Research at the Faculty of Science, University of Lisbon, where he received his PhD in 2002. He has extensively published papers in scientific international journals mostly in the areas of location analysis, supply chain management, logistics and combinatorial optimization. He has been awarded several international prizes such as the EJOR top cited article 2007--2011 (2012) and the prize Roger-Charbonneau (2020) by HEC Monteréal, Quebec, Canada. He is member of several international scientific organizations such as the EURO Working Group on Location Analysis of which he is one the past coordinators. Currently, he is the editor-in-chief of Computers & Operations Research and also member of the editorial advisory board of the Journal of the Operational Research Society (UK) and Operations Research Perspectives. His research interests include discrete optimization, optimization under uncertainty, location theory, and project scheduling.