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Managing under uncertainty is not easy, especially when you’re facing new realities that have never been experienced before. How can you do proper forecasting for your business without relevant historical data? Simulation is the tool to help you with that.

Simulations at the enterprise level are becoming a more widespread and integral part of daily workflows. They are a key component of the insight-generation ecosystem alongside BI, AI, and optimization technologies.

This blog post summarizes the AnyLogic Private Cloud platform and introduces the recording with Q&A session for the webinar AnyLogic Private Cloud: Enabling Enterprise Scale Simulation Deployment.

The recent AnyLogic User Group Session brought together simulation specialists and AnyLogic developers for presentations and discussion.

Presentations for AnyLogic 8, AnyLogic 9, AnyLogic Cloud, and Machine Learning (ML) included live demonstrations and were each followed with in-depth live questions and answers. Here they are.

Before a festive break code freeze, updates for both AnyLogic and AnyLogic Cloud arrived. Contained within them were several improvements that we'll take a look at in this blog.

For AnyLogic, we introduced new rack functionality for the Material Handling Library and added file output capability for models exported to AnyLogic Cloud. While for AnyLogic Cloud, we added enterprise features, made user experience improvements, and increased security. Let’s take a look!

Even though your business may not involve anything remotely related to farming or agriculture, we believe our modeling approach is useful for demonstrating how an interactive simulation model can be used to improve collaboration and decision making.

Let’s examine a model where we used high-level aggregate data and focused on the interactions between different processes. NB: No animals have been harmed during these simulations.

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!

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.

In 2017, we released AnyLogic Cloud to the public. With a userbase of around 10,000 modelers, it is now the largest public online platform for people working in simulation.

The public version of the service is available to everyone, allowing them to run models and experiments. Online models and experiment results can be shared online and run from a browser. The platform leverages the advantages of cloud computing: this way complex experiments are performed faster than on a regular computer, and the quality of animation depends minimally on the power of your device.

The AnyLogic Cloud version 2.2.x releases have given organizations that use simulation modeling an integrated environment for model management and execution. The new features in these releases upgrade simulation accessibility, security, and performance.

This blog post will look at how simulation models are managed by AnyLogic Cloud and highlight various new features up to the current 2.2.2 release.

Monte Carlo simulation is a mathematical technique that provides accurate estimates when working with uncertainties. It uses randomness to obtain meaningful information and is effective for calculating business risks and predicting failures such as cost or scheduling overruns.

AnyLogic enables Monte Carlo simulation for highly complex systems. With multimethod modeling simulated systems can be complex, dynamic, and non-linear. The results from these simulation models can come from parallel processing and cloud computing and made available in a variety of ways, including via API and custom UI. Learn more...