Production scheduling is the process of maximizing the efficiency of production through the detailed planning of manufacturing operations in the short-term. In this blog post, we will illustrate how exactly this has been done using real-world examples from different industries.
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Simulation for risk management: identify, analyze, and mitigate business risks
Risk management is the process of identifying, assessing, and controlling risks for a business. These risks could stem from a wide variety of sources and if an unforeseen event blindsides your business, it could sustain a financial loss. Simulation is a tool that helps identify potential risks and find ways to make your business resilient.
Healthcare simulation: from hospital design to mass vaccination
Healthcare simulation shows hospitals’ capacity and resource utilization, helps identify challenges, and leads to the right solutions based on the analysis of test results. Simulation modeling was frequently and successfully used during COVID-19 for evaluating disease spread and mass vaccination. Read in this blog post how simulation is used to accomplish healthcare-related tasks.
Scaling AnyLogic Models for Mass Runs and Sub-Second Responses
More runs, more users, and more model. More and more is demanded of simulation models as clients analyze greater numbers of scenarios, expand user access, and model in greater detail. How to scale and meet these demands?
PwC emerging technology senior manager Sindy Ma is an expert on scaling simulations. Her presentation at the AnyLogic Conference 2021 showed three real-world case studies of projects that met the challenge of scaling simulations for more scenarios, more users, and more model. Find out more...
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.
COVID-19 and Simulation
One of the key methods for gaining insight into the unknowns of the COVID-19 pandemic is to use simulation modeling. This is true for many disciplines across business and research, as reflected in the collection of public models being uploaded to AnyLogic Cloud. Here we gather a variety of COVID-19 related simulation models.
See the models and try them out!
COVID 19: The Good, the Bad and the Agent Based Model
Why is it so hard to model the COVID-19 epidemic? In this guest blog Ignacio Brottier and Patricio Pipp look at how agent-based simulation modeling goes beyond traditional SEIR and its shortfalls.
The first step to understanding any system is asking ourselves what it is we are trying to understand and, as the team of FiveThirtyEight well explains in their very recommended article, understanding COVID-19’s evolution is no easy task...
Q&A: Hybrid Dynamic Models in COVID-19 Planning and Beyond
The webinar Hybrid Dynamic Models in COVID-19 Planning and Beyond drew in a record number of attendees and prompted some great questions around the theme of simulation modeling and healthcare planning.
Dr. Nathaniel Osgood, a Professor in the Department of Computer Science and Associate Faculty in the Department of Community Health & Epidemiology at the University of Saskatchewan, provided great insight into simulation modeling related to healthcare. Read on for the webinar details, recording, and Dr. Nathaniel Osgood’s Q&A answers.
Early insight into Coronavirus spread in China
Our AnyLogic partners in China obtained a paper relating to COVID-19 and permission to publish a translation.
Writing this now, there is obviously a lot of interest surrounding the spread of the COVID-19, the coronavirus disease. The paper studies the prevalence of infection in a population using agent-based simulation and looks at the importance of factors such as the frequency of close contact among a population.
Getting old – virtually! Modeling the mechanisms of aging.
Timothy E. Hoffman, Katherine J. Barnett, Lyle Wallis and William H. Hanneman of the Center for Environmental Medicine, Colorado State University are to be published in the October 2017 issue of the peer-reviewed Aging Cell journal of the Anatomical Society.
The aim of their investigation was to assess recent significant and unusual research observations regarding aging.