Discrete Event

Discrete event systems (DES) model systems that evolve through a sequence of distinct events, focusing on the timing and order of these events rather than continuous changes. Current research emphasizes developing efficient simulation tools (like SimPy) and novel model architectures such as Petri nets integrated with reinforcement learning, to optimize complex systems like manufacturing processes and robotic coordination. This field is crucial for improving the design, analysis, and control of various systems, with applications ranging from semiconductor fabrication to job shop scheduling and online fault diagnosis in automated production.