Blog

Solving the Bin Packing Problem in warehousing and logistics – strategy comparison


Solving the Bin Packing Problem in warehousing and logistics – strategy comparison

When packing a container, every square inch of empty space is a money loss – either for you or your company. In warehousing and logistics, filling a container with items as tight to each other as possible to reduce the number of containers is a big deal. Decision Lab took it upon themselves to identify what techniques would help make packing quicker and more efficient. Read to learn more about the project and its results.

Streamlining the connection to trained ML models with the ONNX Helper Library


Streamlining the connection to trained ML models with the ONNX Helper Library

There are many cases where it’s desirable to incorporate trained machine learning (ML) models into a simulation model. Now, thanks to a new AnyLogic library, using ONNX ML models is easier and more efficient.

By incorporating this add-on library into your AnyLogic environment, your models can access its functionalities, just like with any other built-in library. It’s simply a matter of adding the helper object to your model and configuring it. Read on to find out more.

Don’t try deep reinforcement learning without this


Don’t try deep reinforcement learning without this

Automated systems have reached their limits and companies wanting to further enhance business processes are turning to artificial intelligence (AI) technologies like machine learning (ML). In an AnyLogic workshop, Microsoft Autonomous Systems Principal Program Manager Kence Anderson explored the advanced decision-making possibilities of ML and showed how Microsoft’s machine teaching concept is achieving faster training times.

The easily accessible workshop session provides a high-level overview of AI’s state of the art with examples from Microsoft and DeepMind research, as well as illustrative Karate Kid analogies.

Pathmind Reinforcement Learning for Simulation webinar


Pathmind Reinforcement Learning for Simulation webinar

Pathmind is a platform that enables AnyLogic users to integrate reinforcement learning into their AnyLogic simulations. This webinar demonstrates how to set up Pathmind reinforcement learning in an AnyLogic model and train an AI policy in the Pathmind web application. We also share two example models that showcase how reinforcement learning can outperform baseline heuristics and other optimization tools.

Find out more, see the webinar recording, and learn from the example models.

Pathmind Reinforcement Learning Experiment in AnyLogic 8.7.4


Pathmind Reinforcement Learning Experiment in AnyLogic 8.7.4

A new experiment in AnyLogic 8.7.4 links to Pathmind’s reinforcement learning (RL) platform, helping simulation modelers and artificial intelligence practitioners lever the synergy between simulation and AI. For large-scale and complex systems, solutions utilizing the Pathmind RL platform are outperforming well-established heuristics.

This blogpost highlights two industrial case studies from Engineering Group that use the Pathmind RL platform and introduces the integrated AnyLogic Pathmind experiment.

Product Delivery Reinforcement Learning


Product Delivery Reinforcement Learning

Accenture partnered with San Francisco based AI company Pathmind to investigate the potential of new reinforcement learning (RL) opportunities in simulation.

The results obtained were extremely good. The method produced a waiting time more than 4x shorter than the Nearest Agent heuristic.

In this blog post, Agustin Albinati summarizes the model, introduces the three key considerations when defining the neural net, and presents the results of his team's investigations. Linked at the end of the blog post is a step by step how-to with Pathmind. Read on!

Q&A: COVID-19 Mass Vaccination — Simulation, AI Application and Real-World Implementation


Q&A: COVID-19 Mass Vaccination — Simulation, AI Application and Real-World Implementation

As COVID-19 vaccines have become available, many challenges have needed resolving. Not least, ensuring sufficient supply and effective distribution.

At our webinar, March 2021, guest presenter Dr. Ali Asgary of York University, Canada, gave insight into the development and use of a drive-through mass COVID-19 vaccination simulation. He provided details of its machine learning model and online application, including how public authorities are using the results in their vaccination rollouts. Here are the webinar details, recording, and Q&A answers.

Predictive Analytics using simulation models


Predictive Analytics using simulation models

In this article, we introduce the broad field of predictive analytics, its connection with machine learning, and how simulation works as a predictive analytics technology.

Why use predictive analytics? Good question. Predictive analytics is about making forecasts based on historical data. Practitioners analyze past events with statistical algorithms and machine learning techniques to produce probabilities and predictions for systems in the future. Almost everyone is subject to and may benefit from predictive analytics. Learn more...