Integer Programming Modeling of Convex Subsets and Related Shape Requirements Many planning and location problems in forestry, mining, political districting, farmland consolidation, as well as in data mining, entail the selection of a subset, or a partition into subsets, that should satisfy some, often ill-specified, shape constraints. A typical such shape constraint is that the […]
Effective scenarios in distributionally robust stochastic programs Traditional stochastic programs optimize the expected value of some function that depends on the decision variables as well as on some random variables that represent the uncertainty in the problem. Such formulations assume that the probability distribution of those random variables is known. However, in practice the probability […]
On Big Data, Optimization and Learning In this talk I review a couple of applications on Big Data that I personally like and I try to explain my point of view as a Mathematical Optimizer — especially concerned with discrete (integer) decisions — on the subject. I advocate a tight integration of Machine Learning and […]
On the Optimal Design of a Bipartite Matching System In this talk, we explore the optimal design of matching topologies for a multi-class multi-server queueing system in which each customer class has a specific preference over server types. We investigate the performance of the system from the perspective of a central planner who must decide the set of […]