Technology Workshops

Take advantage of these pre-conference workshops for a hands on demonstration of the latest in Analytics software. All attendees are welcome to join onsite or pre-register through the self-service center. Descriptions Below


Sunday, April 26, 11am-12:45pm
Room: Cottonwood 4

Sculpting Accreditation Criteria for Data Science/Analytics

Presented by:  Larry Jones, Paul Leidig, and Barbara Price – representing ABET Taskforce

The data science/analytics field has experienced unprecedented growth over the past few years, as organizations across the globe continue to ramp up the hiring of qualified personnel.  Several institutions have created their own versions of data science/analytics programs at the bachelors and master’s levels. Entities such as the ACM, NSF and the National Academies have attempted to define curriculum for baccalaureate programs to begin the development of a shared understanding of the discipline.

A taskforce representing diverse constituents has been exploring possible ABET accreditation criteria for data science programs. ABET accredits programs in applied and natural science, computing, engineering and engineering technology.

This hands-on workshop session will allow attendees to contribute to this effort and will include project objectives, work to date, analysis of stakeholders, project scope, timeline of key deliverables, strawman data science program criteria, time to review and refine the strawman criteria, and identify programs interested in accreditation.


Sunday, April 26, 3-4:45pm
Room: Cottonwood 7

End to End Supply Chain Planning with AIMMS

Learn how you can bring the power optimization to your business with our ready-to-configure SC Navigator applications including

  • Demand Forecasting
  • Network Design
  • Supply & Operations Planning

We will showcase how you can quickly get started on one or more of these connected apps to optimize your supply chain operations. We will also demonstrate the capabilities of our optimization modelling environment, AIMMS Developer for those with the need for bespoke models like scheduling, routing etc.

  • Build custom applications in a user friendly IDE
    • Object oriented design for optimization models
    • WebUI to develop frontend for business users
    • Collaborative development and rapid prototyping
  • Integrate with applications built in Java, C# etc., or data science models in Python, R 

Sunday, April 26, 3-4:45pm
Room: Cottonwood 8

Adding Optimization to Your Applications, Quickly and Reliably: From Prototyping to Integration with AMPL

Presented by: Robert Fourer

Optimization is the most widely adopted technology of Prescriptive Analytics, but also the most challenging to implement:

  • How can you prototype an optimization application fast enough to get results before the problem owner loses interest?
  • How can you develop optimization-based procedures to get results you can use, within your time and resource requirements?
  • How can you integrate optimization into your enterprise’s decision-making systems?

In this presentation, we show how AMPL gets you going without elaborate training, extra programmers, or premature commitments. We start by introducing model-based optimization, the key approach to streamlining the optimization modeling cycle and building successful applications today. Then we demonstrate how AMPL’s design of a language and system for model-based optimization is able to offer exceptional power of expression while maintaining ease of use. To show the power of the model-based approach, we next take a single example through successive stages of the optimization modeling lifecycle:

  • Prototyping in an interactive command environment.
  • Development of optimization procedures via AMPL’s built-in scripting language.
  • Integration through APIs to widely used programming languages, including C++, C#, Java, and MATLAB, and featuring the popular data science languages Python and R.

Our example is simple enough for participants to follow its development through the course of this short workshop, yet rich enough to serve as a foundation for appreciating model-based optimization in practice. We conclude with several case studies from successful business applications.


Sunday, April 26, 11am-12:45pm
Room: Cottonwood 1

Applying AnyLogic Simulation to Solve Various Business Challenges

Presented by: Jeffrey Wirtz, Program Support Specialist, AnyLogic North America

Take a journey through state-of-the-art simulation technologies and see demonstrations of simulation modeling at work in domains such as Manufacturing, Healthcare, Supply Chain, Railway, Oil and Gas, Human Resources, Pedestrian movement and Road Traffic. During the workshop, we will discuss different simulation methodologies (Discrete Event, Agent Based, System Dynamics) and how you can use them in any combination (Multimethod modeling). We will showcase how multimethod models produce more realistic and useful information and have the potential to provide more elegant architecture. We also showcase vertical libraries of AnyLogic, such as modeling sophisticated conveyor networks and Automated Guided Vehicles (AGVs) with the new Material Handling Library. Lastly, We will demonstrate how to fully leverage AnyLogic Cloud when running complex multiple-run experiments such as Monte-Carlo and Parameter Variation.


Sunday, April 26, 1-2:45pm
Room: Cottonwood 7

Nonlinear Optimization Using Artelys Knitro

Presented by: Richard Waltz, Senior Scientist, Artelys Corp,

Nonlinear optimization is used in many applications in a broad range of industries such as economy, finance, energy, health, 3D modeling, and marketing. With multiple algorithms for both continuous and mixed-integer nonlinear optimization, and great configuration capabilities, Artelys Knitro is the leading solver for nonlinear optimization and demonstrates high performance for large scale problems. This session will introduce you to Artelys Knitro, its key features and modeling capabilities, with a particular emphasis on the latest major developments, including a new interface to the Julia programming language and JuMP optimization modeling language. We will work through some tutorial application examples to demonstrate how to use Knitro in a variety of environments.


Sunday, April 26, 9-10:45am
Room: Cottonwood 2

Prototype, develop, deploy and monitor your applications with next-gen IBM DOC

Presented by: Giulia Burchi, Patrice Oms

About next-gen IBM DOC

Next-gen IBM DOC Provides an enterprise platform that helps you build, deploy and run fully scalable decision support applications.

IBM DOC v4 relies on state-of-the-art, open-source technology, and is ready to be configured and customized. It significantly reduces the effort, time and risk associated with creating tailored solutions.

About the Workshop

In this workshop, we will be showing how IBM DOC can provide end-to-end support to all phases of an optimization application development.


Sunday, April 26, 9-10:45am
Room: Cottonwood 1

Deploying models with GAMS MIRO

Presented by: Steven Dirkse and Adam Christensen (GAMS Development Corp)

Are you developing models and looking for a web-based deployment with visualization of input and output data? Does your enterprise require a graphical user interface so that planners can work more productively, leveraging the full potential optimization brings? During this tutorial we introduce GAMS MIRO, a completely new web interface for your GAMS models. We first explain the fundamental concepts of GAMS and the advantages of using GAMS to build optimization-based decision support applications. We also look at existing options to connect GAMS models to other applications and briefly cover some recent developments. The tutorial centers on the recently-released GAMS MIRO. With its tight connections to GAMS, MIRO allows you to perform data manipulation, scenario management, visualization of the model inputs and results, and much more – all from within the web browser – all by adding a very few annotations to your model. You specify which input and output datasets you want to visualize and MIRO produces a fully functional GUI that can be customized to individual tastes and requirements.

During model/application development MIRO can be launched directly from GAMS Studio or from the command line. To fully illustrate the typical MIRO application development workflow, we also show how to deploy an app so that it is available to an end user.

GAMS MIRO also facilitates the generation, organization, and sensitivity analysis of multiple scenarios of an optimization model. A server version will support additional features: managing multiple optimization models for concurrent users with access management, load balancing, batch configuration and much more.

Gurobi Optimization

Sunday, April 26, 3-4:45pm
Room: Cottonwood 1

Recent Developments in Gurobi Optimizer 9.0

This workshop will give an overview of the improvements and new features in the upcoming Gurobi 9.0 release. We’ll talk about our new non-convex MIQCP solver, including a demo that shows how it can find globally optimal solutions to classical bilinear pooling models. We will also discuss significant new enhancements made to our Python interface and show a resource management demo that illustrates the use of optimization and machine learning together.


Sunday, April 26, 9-10:45am
Room: Cottonwood 3

Update on IBM Decision Optimization

Presented by: Speakers: Xavier Nodet, Program Manager, Development of CPLEX, IBM and Sumeet Parashar, Sr. Offering Manager, Decision Optimization/CPLEX, IBM

CPLEX Optimization Studio 12.10 was released in December 2019, and this talk will provide an overview of these recent development. With this new version, CP Optimizer now has callbacks to monitor the state of the search, and can track Key Performance Indicators. CPLEX got a BRANCHING context in the new Generic Callback. And the performance of both engines were significantly improved, specifically for feasibility problems in CP Optimizer, and MIQCP and Benders in CPLEX, with respective speedups of 5x, 1.9x and 2.8x. IBM’s Datascience Platform ( Watson Studio / Watson Machine Learning / Cloud Pak for Data) includes IBM Decision Optimization (CPLEX) as a critical differentiator for the datascience market. In this presentation, we will showcase 1. How Datascientists / OR specialist can make use Watson Studio + CPLEX for model building ; and 2. How Watson Machine Learning (WML) can provide the cloud deployment platform for CPLEX Optimizaton models. We will cover the latest feature updates, roadmap and synergy between on-prem as well as cloud development and deployment.

FICO® Xpress Optimization

Sunday, April 26, 3-4:45pm
Room: Cottonwood 9

Calling all OR Heroes: Learn How to Model and Deploy Solutions in 75% Less Time with FICO® Xpress Insight

Presented by: Baykal Hafizoglu

Join our hands-on workshop to experience how FICO® Xpress Insight helps you read data in any format from any source, integrates with your own machine learning and solvers (or Xpress Solver), enables collaboration with business users, deploys decision support or automated solutions in the cloud or on premises —and does it all in 75% less time.

  • Get the overview of the great new features of FICO® Xpress Solver, Mosel, Workbench, and Insight.
  • Discover the new View Designer, which reduces GUI development times from minutes to seconds.
  • Experience Xpress Insight first-hand, including the power of Xpress Mosel—the premier mathematical modeling, analytic orchestration and programming language.
  • Learn through real-world business examples how developers integrate their own solver(s) with the powerful Xpress Insight platform.
  • See how the flexible, free-to-use Xpress Mosel modeling and programming language allows you to make your solver available to thousands of other Mosel users.

All attendees will receive a link to the complimentary FICO® Xpress Optimization Community License.

Frontline Solvers

Sunday, April 26, 3-4:45pm
Room: Cottonwood 3

How to Succeed with Analytics in the Microsoft Cloud

Presented by: Daniel Fylstra, President

See how easily you can take your analytics project all the way from “bright idea” to widespread use and ROI at this workshop, with RASON V2020: the best way to create, deploy and manage analytics-powered decision models in Microsoft Azure, Office 365, Dynamics 365 and Power Platform. RASON empowers you to create and solve a model – using optimization, simulation and/or machine learning – then to deploy that model for use by co-workers or even customers, taking advantage of “low-code / no-code” tools like Power BI, Power Apps and Power Automate. Finding, cleaning, and securing the data your model needs – once the most time-consuming part of analytics projects – is easy when your data is in the Common Data Service, OneDrive for Business, or non-Microsoft data sources with CData Cloud Hub. Accessing your analytic model results in other software, without programming, is also easy thanks to RASON’s rich OData support. And managing and monitoring performance of your model – often overlooked – becomes easy when it’s hosted in RASON. You’ll learn how RASON as a modeling language and REST API, Analytic Solver for Excel, and Solver SDK for programming languages all work together synergistically to save you time, and support analytics projects across your company.

JMP, a Division of SAS

Sunday, April 26, 1-2:45pm
Room: Cottonwood 3

Statistical and Data Visualization Tools to Simplify Complex Problems

Presented by: Kevin Potcner

With the explosion in availability and use of data across all businesses, students seeking employment in today’s job market should possess a much broader and deeper proficiency in analyzing data than students entering the job market only a short time ago.

The standard 1-sample and 2-sample inferential statistical techniques taught in traditional statistics courses does not fully prepare students for the types of problems they will most likely encounter. And programming environments such as R and Python, though appropriate for many problems, are often not the best tools for many others. Often the best approach to uncovering features in data is to quickly and interactively explore that data by trying a wide variety of analyses, models, and visualization techniques that can handle many variables simultaneously.

In this session, Kevin Potcner – a statistical scientist from JMP – will illustrate a variety of tools that make analyzing complex data easy and fast.

Teachers will see examples of how analyzing data in an interactive software environment quickly brings the data to life and can excite students in the complete data exploration process. Students will learn best-practices in analyzing data in today’s business and industrial environments pick up valuable lessons the presenter has learned during his career as a statistical consultant.

LINDO Systems, Inc. 

Sunday, April 26, 3-4:45pm
Room: Cottonwood 2

Announcing New Versions of LINGO, LINDO API 13, and What’sBest!

Presented by: Linus Schrage
Come and learn about the extensive performance and feature enhancements available in the new releases of the optimization modeling tools LINDO API, LINGO, and What’sBest!.

Enhancements to the Linear Programming Solver include an order of magnitude improvement in performance in solving “long skinny” LP’s with many more variables than constraints. Speed in solving LPs with multiple cores using the concurrent solver has been significantly improved. The newly added Parameter Tuning Tool helps find the best parameter settings for a given set of models. Improvements to the Global Solver include substantially expanded ability to recognize convexity and exploit it to find globally optimal solutions much faster; much improved performance on non-convex quadratic problems. Additional interfaces have been added to support more popular modeling frontends. LINGO has added powerful but easy to use new features to more closely integrate your optimization models into Excel spreadsheets. LINGO has expanded the file types that it can read and write. LINGO’s ability to work with dynamic sets is much improved. The Stochastic optimization capabilities have been improved with enhanced management of large numbers of scenarios. What’sBest! has been enhanced to give more robust support to the wide range of mathematical functions in Excel.

MemComputing, Inc. 

Sunday, April 26, 11am-12:45pm
Room: Cottonwood 2

Solving Integer Linear Programming Problems with MemComputing

Presented by: Fabio Traversa

This workshop will give an overview of MemComputing from a technical perspective, as well as a live demo of the MemCPU™ XPC SaaS. Recent advancements in our mathematical programming solver will be discussed as well as near-term features that users will have access to such as Max-Sat, Quadratic Programming, & QUBO problem solvers.

In addition, recent advancements using MemComputing techniques to accelerate the training of deep neural networks will be covered.

Optimization Direct

Sunday, April 26, 11-12:45pm
Room: Cottonwood 8

How to Deploy applications that combine machine learning/deep learning tools and optimization technologies such as CPLEX/ ODH|CPLEX

Presented by: Robert Ashford & Alkis Vazacopoulos

Organizations are increasingly hiring Data Scientists with Open Source skills. They leverage the capabilities and work with Open Source tools like R, Python, Spark, as well as integration with CPLEX and large data. Come learn how to integrate with Open Source tools to enable clients to get the best of both worlds (Open Source programming and the Modeler GUIs for those who prefer not to code).

Furthermore, we will review the latest developments/results in CPLEX Optimization Studio and the new ODH|CPLEX.

Princeton Consultants

Sunday, April 26, 11am-12:45pm
Room: Cottonwood 7

Optimization Project Risk Management: an Interactive Workshop 

Presented by: Patricia Randall, PhD Director Princeton Consultants

Practitioners recognize that some optimization projects fail, even those that promise significant financial and operational benefits. Princeton Consultants has distilled 20 scorable risk factors, “The Princeton 20”, that describe the core challenges of bringing optimization into fully deployed production. By helping identify and manage common business and technical struggles for projects, this framework leads to successful deployments and best practices for life-cycle management. In this workshop, Dr. Randall will describe its use through real-world examples from a variety of industries and problem areas. During the workshop, attendees will be invited to score in real-time their own projects through the Princeton 20. Dr. Randall will facilitate a group discussion of mitigation strategies for select projects and common risk factors encountered in today’s optimization projects.

Provalis Research

Sunday, April 26, 1-2:45pm
Room: Cottonwood 1

Text Analytics: A Powerful Tool, but not Magic

Presented by: Normand Peladeau

We will give the audience a basic understanding of text analytics by tracing its history, the latest developments, what it can and cannot do for data scientists and where we see it going. This will involve a look at qualitative analysis, content analysis, text mining and machine learning. We will explain how they can be used separately or together to analyze unstructured data. We will discuss when one technique may be more appropriate than another and how they can work together in a mixed methods approach.

Rockwell Automation

Sunday, April 26, 11am-12:45pm
Room: Cottonwood 3

Introduction to Arena Simulation

Presented by: Melanie Barker & Nancy Zupick

Visit before this session to download a trial version of the software. During this workshop, we’ll be demonstrating some basic models in Arena and giving you time to try them yourself. Our goal is to explain the paradigm that our software uses for modeling and communicate what we believe to be the most critical concepts for users to understand. At the end of the session, we’ll do a brief demonstration of the latest version of Arena still in development.


Sunday, April 26, 3-4:45pm
Room: Cottonwood 4

Solving Business Problems with SAS Analytics and OPTMODEL

Presented by: Rob Pratt, Senior R&D Manager Natalia Summerville, Senior R&D Manager Ed Hughes, Principal Product Manager  

SAS offers diverse analytic capabilities, including data integration, statistical analysis, data and text mining, machine learning, artificial intelligence, forecasting, optimization, scheduling, and simulation. The OPTMODEL procedure from SAS provides you with a full-featured optimization modeling language, access to a diverse set of solvers, and the ability to create and use customized solution algorithms. SAS analytic capabilities are also available through the cloud-enabled, open design of SAS® Viya®. You can program in SAS or in other languages—Python, Lua, Java, and R.

We’ll explore analytical and optimization case studies drawn directly from our work with SAS users in a wide range of industries. These case studies demonstrate PROC OPTMODEL’s power and versatility in building and solving optimization models and illustrate how deeply optimization integrates with the full array of analytics provided by SAS.

SAS Academic Programs

Sunday, April 26, 1-2:45pm
Room: Cottonwood 2

SAS Viya and SAS Viya for Learners: Full Analytics and Data Science Technology Stacks

Presented by: James L. HarrounData Science Initiatives Manager, SAS Institute

SAS Viya provides wrap-around support for individual analysts and data science teams though an integrated, open platform that unifies an entire palette of data science tools within a central entry point. Users have access to highly interactive data visualization, workflow, coding, and open source interfaces to leverage the right technologies in the right contexts. Move with confidence through the entire analytics lifecycle to bring together traditional approaches, class-leading in-memory analytics, and open source techniques to answer questions in record time. Educators can request access to SAS Viya for Learners and build an entire curriculum around this technology at no cost. Please attend this session to learn more about Data Science and Analytics using SAS Viya and how SAS Viya for Learners supports classroom instruction of the full Data Science technology stack.

Simio Simulation & Scheduling Software

Sunday, April 26, 1-2:45pm
Room: Cottonwood 4 

New Innovations: Cloud Computing, Real-Time Scheduling, Industry 4.0, and More

Presented by: Renee Thiesing and Katie Prochaska (Simio LLC)

With Simio leveraging the cloud computing power of Microsoft Azure to support your most demanding applications, its compatibility with Schneider Electric’s Wonderware to allow detailed production scheduling with real-time data and risk analysis, and ability to schedule and reschedule in real-time, Simio is leading the way in Industry 4.0 and creating a digital factory. Outside our immense technology partner advances, we have great new features, application areas and capabilities! Come explore an overview of the new Simio experience and see why we are always “Forward Thinking.”