A non-heuristic distributed algorithm for non-convex constrained optimization
| dc.contributor.author | Matei, Ion | |
| dc.contributor.author | Baras, John | |
| dc.date.accessioned | 2013-02-18T15:44:35Z | |
| dc.date.available | 2013-02-18T15:44:35Z | |
| dc.date.issued | 2013-02-15 | |
| dc.description.abstract | In this paper we introduce a discrete-time, distributed optimization algorithm executed by a set of agents whose interactions are subject to a communication graph. The algorithm can be applied to optimization problems where the cost function is expressed as a sum of functions, and where each function is associated to an agent. In addition, the agents can have equality constraints as well. The algorithm can be applied to non-convex optimization problems with equality constraints, it is not consensus-based and it is not an heuristic. We demonstrate that the distributed algorithm results naturally from applying a first order method to solve the first order necessary conditions of an augmented optimization problem with equality constraints; optimization problem whose solution embeds the solution of our original problem. We show that, provided the agents’ initial values are sufficiently close to a local minimum, and the step-size is sufficiently small, under standard conditions on the cost and constraint functions, each agent converges to the local minimum at a linear rate. | en_US |
| dc.identifier.uri | http://hdl.handle.net/1903/13672 | |
| dc.language.iso | en_US | en_US |
| dc.relation.isAvailableAt | Institute for Systems Research | en_us |
| dc.relation.isAvailableAt | Digital Repository at the University of Maryland | en_us |
| dc.relation.isAvailableAt | University of Maryland (College Park, MD) | en_us |
| dc.relation.ispartofseries | TR_2013-02; | |
| dc.subject | distributed optimization | en_US |
| dc.subject | non-convex optimization | en_US |
| dc.title | A non-heuristic distributed algorithm for non-convex constrained optimization | en_US |
| dc.type | Article | en_US |