7 citations · 18 across the 17 of their papers we have counts for
7 papers · 1 filter
Robustness certificates in data-driven non-convex optimization with additively-uncertain constraints
Alexander J Gallo, Massimiliano Zoggia, Alessandro Falsone +2
We consider decision-making problems that are formulated as non-convex optimization programs where uncertainty enters the constraints through an additive term, independent of the d…
On the sensitivity of linear resource sharing problems to the arrival of new agents
Alessandro Falsone, Kostas Margellos, Jacopo Zizzo +2
We consider a multi-agent optimal resource sharing problem that is represented by a linear program. The amount of resource to be shared is fixed, and agents belong to a population…
Energy management for building district cooling: a distributed approach to resource sharing
Fabio Belluschi, Alessandro Falsone, Daniele Ioli +3
This paper deals with energy management in a district where multiple buildings can communicate over a time-varying network and aim at optimizing the use of shared resources like st…
A relaxation technique to ensure feasibility in stochastic control with input and state constraints
Luca Deori, Simone Garatti, Maria Prandini
We consider a stochastic linear system and address the design of a finite horizon control policy that is optimal according to some average cost criterion and accounts also for prob…
Finite time distributed averaging over ring networks
Alessandro Falsone, Kostas Margellos, Simone Garatti +1
We consider a multi-agent system where each agent has its own estimate of a given quantity and the goal is to reach consensus on the average. To this purpose, we propose a distribu…
Dual decomposition for multi-agent distributed optimization with coupling constraints
Alessandro Falsone, Kostas Margellos, Simone Garatti +1
We study distributed optimization in a cooperative multi-agent setting, where agents have to agree on the usage of shared resources and can communicate via a time-varying network t…
Distributed constrained optimization and consensus in uncertain networks via proximal minimization
Kostas Margellos, Alessandro Falsone, Simone Garatti +1
We provide a unifying framework for distributed convex optimization over time-varying networks, in the presence of constraints and uncertainty, features that are typically treated…