Abstract: Networked CPS systems are a class of complicated physical systems with inter-connected and coupled sub-systems. By exchanging information via networks, each sub-system can coordinate and optimize their behaviors and make local decisions in order to achieve global tasks. For this class of systems, it is difficult to solve the optimization problems efficiently and adaptively using the classical centralized approaches. Therefore, it is necessary and important to develop novel distributed optimization methods for networked systems. In particular, there is a great demand for such distributed methods in modern distributed networked systems, including smart-grids and sensor networks. In this project, we tackle the difficulties in real-time optimization and decision making of networked systems. By investigating the information exchange mechanisms and the physical couplings between each sub-system, three key problems are formulated:the constrained optimization problem when dynamical coupling, the decision making problem for consensus under multi-task conflict and the adaptive cooperation problem under network topology changes. By adjusting the feasible region of the dynamically-coupled constrained optimization problem, analyzing and predicting the dynamic behavior of each sub-system, and switching the operation mode of the system, we develop a comprehensive framework for real-time optimization and decision making of networked systems. Much progress in the CPS optimization and control has been made, in this paper, some further problems are discussed based on the results of this special issue.