The field of complex system optimization and network analysis is witnessing significant developments, driven by the need to improve the efficiency and resilience of complex systems. Researchers are focusing on innovative approaches to analyze and optimize the behavior of these systems, including the development of new algorithms and methodologies for network embedding, interlayer similarity measurement, and evacuation planning.

A key direction in this field is the integration of external and internal factors to understand and mitigate the effects of overcrowding and congestion in complex systems, such as emergency departments and transportation networks. The use of data-driven approaches, including machine learning and regression analysis, is becoming increasingly prominent in this context.

Another important area of research is the development of optimized evacuation plans for critical scenarios, such as active-shooter situations, using multi-route routing optimization algorithms that account for available capacity along the route. These approaches have the potential to significantly reduce casualties and improve outcomes in emergency situations.

The study of interlayer similarity in multiplex networks is also gaining traction, with the development of new algorithms and frameworks for analyzing interconnected systems. These advances have implications for a wide range of applications, including transportation, social, and biological systems.

Notable papers in this area include:

• A study on assessing the impact of external and internal factors on emergency department overcrowding, which highlights the importance of incorporating both operational and non-operational factors to understand ED patient flow.
• A paper on assessing the robustness and reducibility of multiplex networks with embedding-aided interlayer similarities, which proposes a novel interlayer similarity measuring approach and demonstrates its effectiveness in capturing the underlying geometric similarities between interconnected networks.
• A study on an optimized evacuation plan for an active-shooter situation constrained by network capacity, which develops a multi-route routing optimization algorithm that reduces the total casualties by 34.16% and 53.3% compared to other evacuation algorithms.