In this paper we propose a distributed algorithm for solving linear programs with combinations of local and global constraints in a multi-agent setup. A fully distributed and asynchronous algorithm is proposed. The computation of the local decision makers involves the solution of two distinct (local) optimization problems, namely a local copy of a global linear program and a smaller problem used to generate ”problem columns”. We show that, when running the proposed algorithm, all decision makers agree on a common optimal solution, even if the original problem has several optimal solutions, or detect unboundedness and infeasibility if necessary.
Locally Constrained Decision Making via Two-Stage Distributed Simplex / Mathias Burger; Giuseppe Notarstefano; Frank Allgower. - STAMPA. - (2011), pp. 5911-5916. (Intervento presentato al convegno IEEE Conference on Decision and Control and European Control Conference (CDC-ECC) tenutosi a Orlando, FL, USA nel December 12-15 2011) [10.1109/CDC.2011.6161182].
Locally Constrained Decision Making via Two-Stage Distributed Simplex
Giuseppe Notarstefano;
2011
Abstract
In this paper we propose a distributed algorithm for solving linear programs with combinations of local and global constraints in a multi-agent setup. A fully distributed and asynchronous algorithm is proposed. The computation of the local decision makers involves the solution of two distinct (local) optimization problems, namely a local copy of a global linear program and a smaller problem used to generate ”problem columns”. We show that, when running the proposed algorithm, all decision makers agree on a common optimal solution, even if the original problem has several optimal solutions, or detect unboundedness and infeasibility if necessary.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
