Data collection in application domains like agriculture and environmental science requires the deployment of sensors in large remote areas. These use cases challenge the traditional optimal experimental design (OED) formulation from statistics by their scale as well as the presence of complex operational constraints, such as that data is collected along the trajectory of a … Read more
Cut generation and lifting are key components for the performance of state-of-the-art mathematical programming solvers. This work proposes a new general cut-and-lift procedure that exploits the combinatorial structure of 0-1 problems via a binary decision diagram (BDD) encoding of their constraints. We present a general framework that can be applied to a large range of … Read more
A probabilistic framework for large classes of binary integer programming problems is constructed. The approach is given by a mean field annealing scheme where the annealing phase is substituted by the solution of a dual problem that gives a lower (upper) bound for the original minimization (maximization) integer task. This bound has an information theoretic … Read more