Distributed intelligent scheduling architecture based on cyber-physical system

Over the last few decades, distributed manufacture (DM) with new features attracts peo-ple's attention. Nowadays, DM is customers' indi-viduation-oriented which possess features of high flexibility, high agility, loose coupling and geography discrete organization. With these features, scheduling problem in DM (DMS) becomes much more complex. However, distributed manufacture scheduling plays an important role for the interests of both enterprises and customers. Almost, existing DMS algorithms are either based on heuristic dispatching rules or based on meta heuristic algorithm, while the former is dif-ficult to adapt to flexible and highly distributed production environment and the latter is hard to use for real-time scheduling because of its long compu-ting time. In order to optimizing scheduling objective faster and better for DMS as well as realizing its au-tomation and intelligence, this paper proposes a dis-tributed scheduling system architecture based on cyber physical systems (CPS) and multi-agent tech-nology. Besides, driven by "industrial big data + machine learning", two intelligent scheduling algo-rithm frameworks are designed for different sched-uling stages of DMS.