Node-Based Adaptive Fractional Distributed Optimization Algorithm

Fractional distributed optimization can be applied in many fields and is attracting increasing research interest. This paper presents a node-based fractional distributed optimization algorithm, eliminating the need for a priori knowledge of the global Laplace matrix. It is proved the algorithm can converge to the minimum of the problem. In the end, the paper validates the performance of the algorithm through simulations.