Distributed Multi-Agent Optimization Based on a Constrained Subgradient Method

Abstract

This paper proposes a protocol for a distributed optimization problem to minimize the average of objective functions of the agents in the network with satisfying constraints of each agent. The protocol can handle uncommon constraints of the agents. Instead of invoking dual functions, only 1-bit information on fulfillment of the constraint of each agent is transmitted between agents as well as the decision variable. The proof of consensus and convergence is provided based on the constrained subgradient method. A numerical example illustrates how the proposed protocol works.