Complex large-scale systems arise regularly in various disciplines such as social economy, enterprise management, population resources, ecological environment, power system, communication, and transportation. In general, the operation mechanisms of large-scale systems are difficult to understand because of their complex structure and isomerism. In view of this, the operation management and optimization of complex large-scale systems has always been a challenging problem.

With the rapid development of cloud computing, big data, and especially artificial intelligence technologies, intelligent methods with the model of data and knowledge fusion has become increasingly appealing in the operation and management optimization of complex large-scale systems. Such methods can greatly simplify the model requirements of complex large-scale systems and thus can be widely applied in parameter identification, operation scheduling, and management optimization of large-scale systems. The operation and management of complex large-scale system with the help of intelligent methods has become urgent in both academic and industrial circles.

This Special Issue therefore aims to bring together researchers from either academia or industry to discuss new and existing issues with respect to intelligent methods for complex large-scale systems, in particular, to foster collaboration between academic research and industry applications, and to stimulate further engagement with the user community. Submissions on recent advances of intelligent methods for large-scale systems, and new horizons are welcome, e.g., machine learning methods developed for large-scale system management, scheduling. In addition, we are interested in various studies discussing the real-world large-scale systems, e.g., the hybrid energy system and unmanned swarm system.

Potential topics include but are not limited to the following:

• Multi-objective optimization of complex large-scale systems
• The management of complex large-scale systems under uncertain/dynamic environments
• Optimization problems in complex large-scale systems
• Intelligent modelling and simulation methods for complex large-scale systems
• Multi-criteria evaluation of complex large-scale systems
• Robust optimization approaches for complex large-scale systems
• Multi-criteria decision making techniques for complex large-scale systems
• Deep learning methods in complex large-scale systems
• Complex large-scale system optimization based on evolutionary computation methods
• Real-world case studies of hybrid energy systems, unmanned swarm systems, and networked systems