Handle uncertainty Uncertainty in operations’ time and outcome can be easily represented in simulation models, which allows you to measure risk and find more robust solutions.Increased accuracy A simulation model can capture much more details than an analytical model, which provides for increased accuracy and more precise forecast.E.g., you can check warehouse storage space utilization at any given date. Insight into dynamics Unlike spreadsheet- or solver-based analytics, simulation modeling allows observation of system behavior over time at any level of detail.Visualization Simulation models can be animated in 2D/3D, allowing concepts and ideas to be more easily verified, communicated, and understood. AnyLogic Tutorial The STSA Lab Group wrote a tutorial to guide the user through creation of an agent-based model of a forest fire. With a focus on improving the supply chain decision-making process, Accenture took the AnyLogic Product Delivery example model (also available in AnyLogic Cloud) and used it to prove the power of new reinforcement learning (RL) opportunities.Therefore, they allow inheritance, virtual methods, polymorphism, etc. Save money and time Virtual experiments with simulation models are less expensive and take less time than experiments with real assets. Active object classes map to Java classes.Make the right decision before making real-world changes. The workshop is built around the new features of AnyLogic 8.3. Risk-free environment Simulation modeling provides a safe way to test and explore different “what-if” scenarios. Using the New AnyLogic Material Handling Library and Running Simulation Experiments in the Cloud.
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