DC-DistADMM: ADMM Algorithm for Constrained Distributed Optimization over Directed Graphs

Understand

This article reports an algorithm for multi-agent distributed optimization problems with a common decision variable, local linear equality and inequality constraints and set constraints with convergence rate guarantees.

• \textcolor{black}{The algorithm accrues all the benefits of the Alternating Direction Method of Multipliers (ADMM) approach}.
• It also overcomes the limitations of existing methods on convex optimization problems with linear inequality, equality and set constraints by allowing directed communication topologies.
• Moreover, the algorithm can be synthesized distributively.