This letter proposes a multi-agent distributed solution for linear programming (LP) problems with time-invariant box constraints on the decision variables and possibly time-varying inequality constraints. This class of LP problems is relevant in different multi-agent smart systems. In the proposed approach, each agent computes only a single or a few of decision variables, while convergence to the optimal solution for the overall problem is guaranteed. Using a strong convexification of the problem combined with the barrier method, we prove that, despite the fact that the inequalities are time-varying, the tracking error remains bounded, and the bound is proportional to the rate of change of parameters. The effectiveness of the proposed schem...
The pervasiveness of networked systems in modern engineering problems has stimulated the recent rese...
We identify a novel class of distributed optimization problems, namely a networked version of abstra...
We deal with decision making in a large-scale multi-agent system, where each agent aims at minimizin...
European Control Conference (ECC) -- JUN 12-15, 2018 -- Limassol, CYPRUSWOS: 000467725301078The pape...
In this paper we develop a multi-agent distributed algorithm to solve a quadratic programming proble...
In this paper we propose a distributed algorithm for solving linear programs with combinations of lo...
Abstract—We devise a distributed asynchronous gradient-based algorithm to enable a network of comput...
Many problems of interest for cyber-physical network systems can be formulated as mixed-integer line...
We consider a general class of convex optimization problems over time-varying, multi-agent networks,...
In the article, we study the distributed model predictive control (DMPC) problem for a network of li...
A multi-agent system is defined as a collection of intelligent agents which are able to interact wit...
Network-structured optimization problems are found widely in engineering applications. In this paper...
Abstract. We study combinatorial optimization problems in which a set of distributed agents must ach...
This dissertation studies first a distributed algorithm to solve general convex optimizationproblems...
We deal with decision making in a large-scale multiagent system, where each agent aims at minimizing...
The pervasiveness of networked systems in modern engineering problems has stimulated the recent rese...
We identify a novel class of distributed optimization problems, namely a networked version of abstra...
We deal with decision making in a large-scale multi-agent system, where each agent aims at minimizin...
European Control Conference (ECC) -- JUN 12-15, 2018 -- Limassol, CYPRUSWOS: 000467725301078The pape...
In this paper we develop a multi-agent distributed algorithm to solve a quadratic programming proble...
In this paper we propose a distributed algorithm for solving linear programs with combinations of lo...
Abstract—We devise a distributed asynchronous gradient-based algorithm to enable a network of comput...
Many problems of interest for cyber-physical network systems can be formulated as mixed-integer line...
We consider a general class of convex optimization problems over time-varying, multi-agent networks,...
In the article, we study the distributed model predictive control (DMPC) problem for a network of li...
A multi-agent system is defined as a collection of intelligent agents which are able to interact wit...
Network-structured optimization problems are found widely in engineering applications. In this paper...
Abstract. We study combinatorial optimization problems in which a set of distributed agents must ach...
This dissertation studies first a distributed algorithm to solve general convex optimizationproblems...
We deal with decision making in a large-scale multiagent system, where each agent aims at minimizing...
The pervasiveness of networked systems in modern engineering problems has stimulated the recent rese...
We identify a novel class of distributed optimization problems, namely a networked version of abstra...
We deal with decision making in a large-scale multi-agent system, where each agent aims at minimizin...