How Can Pathmind Help Me With Simulation Optimization?
Pathmind helps businesses find better ways to save money and increase output by using AI for simulation optimization, and then deploying trained AI into operations.
Our web application frees up your time and local resources while it searches for solutions using reinforcement learning and cloud computing clusters.
Once the best decision paths have been found, Pathmind creates an AI policy to embed in your systems.
We offer simulation modelers a quick, simple workflow that requires no advanced knowledge of AI.
Pathmind Product Demo
Take a look at this video to see how Pathmind is used to lower delivery wait times in a network of factories and distribution centers. When faced with real-world complexities, Pathmind outperforms the heuristics and optimizers to generate better results.
Delivery optimization is just one example of how Pathmind gets the most out of simulation models. Check out our other example models to see how Pathmind performs in simulations featuring supply chains, coffee shops, and more.
Why Should I Use AI in Simulations?
Get to Better Results Faster
Get superior results in less time from the tools you trust by using AI and cloud computing for simulation optimization.
Handle Variance and Change
Navigate unexpected change and variance with Pathmind policies that outperform mathematical optimizers.
Deploy Real-Time Decisions
Implement trained predictive AI models in real-world systems to make key decisions better.
Where Do I Start With AI?
Build a model ready for AI simulation optimization using tools that you trust like AnyLogic in a familiar workflow.
Just drag and drop the Pathmind Helper into your model and use its properties to add AI capabilities.
Train your AI models fast on Pathmind’s web app.
Experiment tracking makes it easy to monitor progress and results across multiple experiments.
Deploy validated AI models as endpoints in a REST API to make better decisions.
Query the endpoints to know the AI’s suggested action or decision, which can be easily applied in production.
Summary Princeton Consultants, a simulation consulting firm, serves a manufacturing client with a hard machine scheduling problem. Its optimizer had difficulty scheduling machines for new types of items that needed to be processed; it was not able...
Summary Eurystic, a supply chain optimization and simulation consultant, worked with Pathmind on a simplified model showing deep reinforcement learning could help a crane stacking packages in a warehouse and increase its throughput. Challenge A...
Summary A simulation consultancy worked with Pathmind to apply reinforcement learning to intelligently re-route haul trucks at an open-pit mining site. The mining optimization project discovered a solution that resulted in a 19% increase in ore...