Community detection is a widely-studied unsupervised learning problem in which the task is to group similar entities together based on observed pairwise entity interactions. This problem has applications in diverse domains such is social network analysis and computational biology. There is a significant amount of literature studying this problem under the assumption that the communities … Read more
We investigate the problem of exactly separating cover inequalities of maximum depth and we develop a pseudo-polynomial-time algorithm for this purpose. Compared to the standard method based on the maximum violation, computational experiments carried out on knapsack and multi-dimensional knapsack instances show that, with a cutting-plane method based on the maximum-depth criterion, we can optimize … Read more
In critical node problems, the task is identify a small subset of so-called critical nodes whose deletion maximally degrades a network’s “connectivity” (however that is measured). Problems of this type have been widely studied, e.g., for limiting the spread of infectious diseases. However, existing approaches for solving them have typically been limited to networks having … Read more
We consider the least squares regression problem, penalized with a combination of the L0 and L2 norms (a.k.a. L0 L2 regularization). Recent work presents strong evidence that the resulting L0-based estimators can outperform popular sparse learning methods, under many important high-dimensional settings. However, exact computation of L0-based estimators remains a major challenge. Indeed, state-of-the-art mixed … Read more
The Double Row Layout Problem (DRLP) occurs in automated manufacturing environments, where machines arranged in a double-row layout, i.e. the machines are located on either side of a straight line corridor. The DRLP is how to minimize the total cost of transporting materials between machines. The problem is NP-Hard. In this paper, we give a … Read more
The prize-collecting Steiner tree problem (PCSTP) is a well-known generalization of the classic Steiner tree problem in graphs, with a large number of practical applications. It attracted particular interest during the 11th DIMACS Challenge in 2014, and since then, several PCSTP solvers have been introduced in the literature. Although these new solvers further, and often … Read more
Designing policies for a network of agents is typically done by formulating an optimization problem where each agent has access to state measurements of all the other agents in the network. Such policy designs with centralized information exchange results in optimization problems that are typically hard to solve, require to establish substantial communication links, and … Read more
The ever-widening acceptance and deployment of drones in last-mile distribution continue to increase the need for planning and managing the delivery operations involving drones effectively. Motivated by the growing interest towards drone-assisted last-mile transportation, we study a hybrid delivery system in which (multiple) trucks and (multiple) drones operate in tandem. In particular, we introduce the … Read more
Two-stage stochastic models give rise to very large optimization problems. Several approaches have been devised for efficiently solving them, including interior-point methods (IPMs). However, using IPMs, the linking columns associated to first-stage decisions cause excessive fill-in for the solution of the normal equations. This downside is usually alleviated if variable splitting is applied to first-stage … Read more
Traffic jams cause economical damage which has been estimated between 10 and 100 billion Euros per year in Germany, also due to inefficient urban traffic. It is currently open how the situation will change with upcoming technological advances in autonomous and electric mobility. On the one hand, autonomous cars may lead to an increased number … Read more