Distributed optimization for resource allocation with event-triggered communication under directed topology

This paper focuses on the resource allocation problem with equality and inequality constraints in a fixed weight-balanced directed or undirected network. Moreover, we propose a fully decentralized subgradient algorithm with event-triggered for solving above resource allocation problem based on first-order discrete-time multi-agent systems. Where each agent only communicates with its neighbors and the triggering function only requires local information. The above algorithm aims to minimize the total cost by a distributed manner, that is, each agent updates its state by employing the states collected from itself and its neighboring agents at their last triggering time. Finally, an example is given to analyze the feasibility of the event-triggered algorithm.