Research status and prospects of distributed collaborative optimization

Abstract

Distributed collaborative optimization is the effective implementation of optimization tasks through cooperation and collaboration of multiple agents. The theory and application of distributed collaborative optimization is one of the important development directions in Control Science and Engineering. In recent years, with the development of emerging technologies such as cloud computing, big data, mobile internet, and artificial intelligence, distributed collaborative optimization has been facing new challenges and opportunities. This paper reviews and summarizes some hot research directions of distributed collaborative optimization in recent years, including distributed accelerated optimization algorithms, distributed non-convex optimization algorithms, and distributed gradient-free optimization algorithms. Moreover, guided by three practical applications of intelligent manufacturing, Energy Internet and distributed machine learning, key future research directions of distributed collaborative optimization are prospected.