Vendor Workshops

Vendor Workshops take place on Sunday, December 8 at no additional charge.

Check back for updates on workshop schedule and descriptions!

Applied Materials
Sunday, December 8

Coming Soon

Frontline Solvers
Sunday, December 8

Frontline Solvers Next-Generation Software
Presented by: Daniel H. Fylstra, President

Come see Frontline’s radically new Solver software for simulation, optimization and machine learning plus business rules and decisions. Our Analytic Solver®, fully re-engineered as a cloud-first Office 365 app, works equally well in Excel for the Web, Excel for Windows and Excel for Macintosh.  Our cloud-based RASON® Analytics API and high-level modeling language executes workflows of inter-related machine learning, optimization and simulation models, and decision tables at blazing speeds.  See how our tools enable rapid, low-code or no-code deployment of your analytic models into Power BI, Tableau, PowerApps and Microsoft Flow, inter-operating with your JavaScript, C/C++, C#, Java, R or Python code.

Optimization Firm
Sunday, December 8

ALAMO for data analytics and machine learning
Presented by: Dr. Yash Puranik and Dr. Nick Sahinidis

The Optimization Firm will present the new ALAMO software for building models from data. With innovative optimization and sampling technology, ALAMO uses data from experiments or simulations to generate interpretable models. ALAMO ensures that the models are as simple and accurate as possible while also satisfying physical constraints on the response variables. This workshop will describe ALAMO’s most important features that make it uniquely suited for machine learning and analytics. We’ll also present results comparing ALAMO to standard machine learning methods. Everyone has free access to ALAMO before its commercial launch.

Probability Management
Sunday, December 8

Tutorial in Probability Management – Turning Siloed Simulations into a Collaborative Network
Presented by: Dr. Sam L. Savage, Executive Director of & Shaun Doheney, Chair of Resources and Readiness Applications,

This workshop will demonstrate:

  1. The Open SIPmath™ Standard – Conveying uncertainty as actionable data
  2. Doug Hubbard’s HDR Pseudo Random Number Framework – Ensuring Analytical Coherence
  3. Tom Keelin’s Metalog Distributions – Capturing Uncertainty from Data with Ease

Although platform agnostic, each of these technologies is supported by native Excel without the use of
Macros or Add-ins. If you want to model along in Excel, we suggest downloading the Free SIPmath Tools

  • The Arithmetic of Uncertainty – The Hindu/Arabic Numerals of Uncertainty
  • Limbic Analytics – Connecting the Seat of the Intellect to the Seat of the Pants
  • Aggregating Simulations – Turning Siloed Stochastic Models into a Collaborative Network


Simio Simulation & Scheduling Software
Sunday, December 8

Teaching Simio Benefits
Presented by: Dave Sturrock and Alex Molnar

Why teach with yesterday’s technology in an evolving world? Simio offers you an excellent opportunity to take advantage of emerging technology solutions and apply them in your classrooms. Come learn about Simio and the benefits of teaching with Simio simulation and Digital Twin solutions. This workshop will highlight how Simio can be used to integrate Active Learning in your classrooms. You will also be provided with an overview of Simio and its ability’s to digital transform classroom exercises, course work, and research.

Simio can enhance your lessons and student’s research in STEM-related fields including manufacturing and healthcare. Simio also offers grants, online trainings, and competitions to help your students gain real-world experiences. And no! This isn’t a snake-oil pitch. Simio is currently used in 800 universities worldwide and this is your opportunity to digitally transform your classroom!

Simio Simulation & Scheduling Software
Sunday, December 8

Simio: The True Digital Twin 
Presented by: Dennis Pegden and Gerrit Zaayman

Cloud-computing, real-time scheduling, IIoT, Industry 4.0, and High-performing computers are all emerging technologies you are probably curious about. Is a solution that brings all these technologies together in one environment something you will be interested in using or teaching? Come and explore how Simio leverages the cloud-computing power of Microsoft Azure to support Industry 4.0 and data-driven manufacturing processes. Simio is also compatible with Schneider Electric’s Wonderware which allows for detailed production scheduling and real-time analytics which are staples of Industry 4.0.

You can also explore how Simio can drive your industrial digital transformation projects and simplify the move to Industry 4.0. Also, learn how Industry 4.0 – compliant facilities can collect and make use of data from the deepest sections of manufacturing facilities through the Digital Twin. Come explore an overview of the new Simio experience and features to see why we are always “Forward Thinking.”

The AnyLogic Company
Sunday, December 8

ANYLOGIC Models as Virtual EnvironmentS to Train and Test Artificial Intelligence for Business Applications
Presented by: Andrei Borshchev, Arash Mahdavi, Anatoly Zherebtsov

Although simulation modeling has been around for decades addressing general purpose technical and business applications, the current trends and recent advancements in technology have given significant relevance on a broader scale. In this workshop we will quickly review simulation modeling and the technology progression and consider major current trends including the creation of digital twins and simulation technology in the cloud. Following, we will broaden the discussion of simulation modeling by viewing it as part of AI technology. As today’s AI developers are working on increasingly wide range of business applications, they require a powerful and realistic virtual environment to train and test the learning agents, which naturally creates a new type of demand and requirements for simulation models. We will conclude with major use cases and architectures of how AnyLogic simulation models integrate with machine learning.