Abstract Within the context of solving Mixed-Integer Linear Programs by a Branch-andCut algorithm, we propose a new strategy for branching. Computational experiments show that, on ...
This paper describes a parallelization of the sequential dynamic programming method for solving a 2D knapsack problem where multiples of n rectangular objects are optimally packed...
The problem of learning the structure of Bayesian networks from complete discrete data with a limit on parent set size is considered. Learning is cast explicitly as an optimisatio...
We consider probabilistic constrained linear programs with general distributions for the uncertain parameters. These problems generally involve non-convex feasible sets. We develo...
Abstract. We propose a randomized method for general convex optimization problems; namely, the minimization of a linear function over a convex body. The idea is to generate N rando...
Fabrizio Dabbene, P. S. Shcherbakov, Boris T. Poly...