Proportional integral distributed optimization for dynamic network topologies

This paper investigates proportional-integral distributed optimization when the underlying information exchange network is dynamic. Proportional-integral distributed optimization is a technique which combines consensus-based methods and dual-decomposition methods to form a method which has the convergence guarantees of dual-decomposition and the damped response of the consensus methods. This paper extends PI distributed optimization to allow for dynamic communication networks, permitting agents to change who they can communicate with, without sacrificing convergence to the collective optimum.