Distributed Robust Resource Allocation with Convex-Concave Uncertain Objective Functions

This paper investigates the distributed robust resource allocation problem where the objective function is a convex-concave function with uncertain parameters. To guarantee the robustness, we investigate the worst-case scenario, which results in finding the saddle point of the objective function with the resource constraint satisfied. We deal with this problem by adopting a continuous-time distributed projected algorithm. A numerical example is presented to illustrate the effectiveness of the proposed algorithm.