Distributed Multi-Agent Optimization for Pareto Optimal Problem over Unbalanced Networks via Exact Penalty Methods with Equality and Inequality Constraints

This paper proposes a distributed multi-agent optimization protocol to solve a Pareto optimal problem. The protocol only requires local communications between agents to exchange decision variables and the graph representing the communications has to be only strongly connected but does not need to be balanced. This extends the implementability of the protocol to real-world applications. The protocol is based on exact penalty methods and can handle inequality and equality constraints. The computation is executed without disclosing objective and constraint functions.