Discrete Event Simulation

Discrete event simulation (DES) is a powerful modeling technique used to analyze complex systems by representing them as a sequence of events occurring over time. Current research emphasizes the application of DES across diverse fields, including manufacturing, healthcare, logistics, and finance, often integrating it with machine learning for improved prediction and optimization. This integration allows for more accurate modeling of dynamic systems and enables data-driven decision-making, leading to improved efficiency and resource allocation in various real-world applications. The development of user-friendly tools like SimPy is also broadening DES's accessibility and fostering wider adoption across scientific disciplines and industries.