Exhibitor Workshops

Take advantage of these complimentary, pre-meeting Exhibitor Workshops for hands-on demonstrations of the latest industry products and software. All full conference registrants are welcome to preregister or join on site.

All Exhibitor Workshops will be held in Moscone Center South on Saturday, October 31.

Add Exhibitor Workshops to Your Current Registration
Once logged into your INFORMS account, go to Events in the top-right corner, then select 2026 INFORMS Annual Meeting.

Go to Manage Registration.

Click the three dots to the right of your name.

Select Purchase New Session.

Select the complimentary Exhibitor Workshops you would like to add.

Click Continue.

Follow the prompts to complete the process.

10:30-11:45AM

SAS Optimization, Quantum Computing, Network Analytics, and IoT

Speakers: Rob Pratt, Amy Becker, & Yonggui Yan

Description

SAS offers extensive analytics capabilities, including machine learning, deep learning, natural language processing, statistical analysis, optimization, and simulation. SAS analytics are also available through the open, cloud-enabled architecture of SAS® Viya®. You can program in SAS or in other languages, including Python, Lua, Java, and R.

This workshop will provide an overview of the SAS analytics portfolio and highlight recently added features, including a new mixed integer nonlinear programming (MINLP) solver and SAS Quantum Lab. Additional topics will include network analytics and the Internet of Things (IoT), with examples that demonstrate how you can use these technologies to solve real-world business and operational challenges.

1:30-2:45PM

Analyzing Multidimensional Data in an Interactive, No-code Environment

Speaker: Kevin Potcner

Description

Fully analyzing data requires an analyst to generate a wide variety of visualizations, analyses, and models. The insights gleaned from each step leads the analyst to a next set of analyses to try, and so on. This exploratory approach can become cumbersome in a coding environment. Without strong proficiency in programming, students often get frustrated finding themselves unable to run many different analyses and visualization quickly. In this presentation, a statistical scientist from JMP will illustrate how easy it can be to explore multi-dimensional data through interactive visualizations, analyses, and models in a “no code” environment.

Teaching Business Students to Build AI Applications

Speaker: Tingting “Rachel” Chung

Description

Rachel Chung will provide an extended presentation of various labs, teaching aids, and challenges in teaching business students to develop AI applications. Learning objectives regarding advancing critical thinking and responsible behavior are covered. This presentation is drawn from her new textbook, “AI for Business: Building Applications using Python” from Prospect Press.

3-4:15PM

Model and Solve Nonlinear Optimization Problems with Artelys Knitro

Speaker: Louis-Pierre Campeau

Description

Artelys Knitro is the leading solver focused on large-scale, nonlinear (potentially non-convex), optimization problems. Knitro offers both interior-point and active-set algorithms for continuous models, as well as tools for handling problems with integer variables and other discrete structures. This tutorial will introduce the key features of Knitro, and demonstrate how to use Knitro to model and solve optimization problems in various environments. The talk will showcase several instances of nonlinear problems, typically addressed through linear relaxation, yet warranting a direct approach. It will delve into the methodologies and tools employed to tackle these challenges. This tutorial aims at an audience familiar with the basics of mathematical optimization and Python programming but will mostly be focusing on practical examples.

This is a hands-on tutorial, please bring a computer.

GAMS in Production: Python, Scaling, and Modern Optimization Workflows

Speakers: Atharv Bhosekar, Adam Christensen, & Steven Dirkse

Description

This workshop covers how the GAMS ecosystem has evolved to support modern optimization workflows, including integration with Python, cloud deployment, and AI tooling. Presenters will walk through GAMSPy for Python-based modeling, GAMS Connect for moving data between systems, GAMS Engine for scaling computationally demanding models, and MIRO for building web-based interfaces that put optimization results in front of decision-makers. The session also touches on emerging AI integrations where they complement existing workflows. Presenters will also address real trade-offs encountered in production, performance tuning, and maintaining large models over time.

From Optimization to Intelligence: What’s New in Gurobi 14 and the Future of AI

Speakers: Oliver Bastert, Robert Luce, & Lindsay Montanari

Description

Discover the latest innovations in Gurobi Optimizer 14 and explore how optimization is evolving alongside generative AI. This interactive session will provide an overview of new capabilities, introduce the Gurobean game, and showcase how Gurobi’s GAIL team is applying AI to help users solve complex decision-making challenges. Bring your questions for an open discussion with Gurobi experts.

Hexaly, Beyond Traditional MIP

Speaker: Fred Gardi

Description

Mixed-Integer Programming (MIP) has been the dominant optimization framework in Operations Research for several decades. While highly effective, classical MIP formulations can become increasingly difficult to express and solve as problems grow in scale and structural complexity, particularly in domains such as routing, scheduling, and packing.

Hexaly is a next-generation optimization solver designed to extend the scope of traditional MIP. Rather than relying solely on linearization and standard branch-and-bound workflows, it provides a unified framework for modeling and solving combinatorial and nonlinear problems in a more natural way. By integrating techniques from MIP, constraint programming, nonlinear optimization, and black-box optimization within a single engine, Hexaly enables more expressive models while maintaining high solution quality and scalable performance.

This talk will feature the key principles behind this approach, with a focus on large-scale discrete optimization problems where Hexaly performs best, such as routing, scheduling, and packing. It will also show how this extended modeling framework enables problems to be formulated more closely to their underlying structure, while allowing diverse algorithmic components to interact in a complementary manner. Finally, selected benchmark results will illustrate the practical impact of this approach.

4:30-5:45PM

Getting Optimization into Production with AMPL: From Prototype Models to Operational Decision Systems

Speakers: Juan Bohorquez & Christian Valente

Description

Optimization models often start as compact prototypes, but translating them into operational systems introduces significant challenges in scalability, system integration, and solver performance. Using a power generation portfolio optimization example, this workshop demonstrates how to bridge the gap between initial prototypes and production-ready decision applications using AMPL. Starting with a basic linear programming formulation, we progressively expand it toward a realistic industry application, addressing common production barriers such as feasibility management, workflow maintainability, and computational speed. Attendees will explore practical modeling patterns, solver strategies, and integration architectures to overcome deployment bottlenecks and build reliable decision support workflows.

Building Decision Intelligence of the Future: AI, GPU-accelerated Optimization, and Model Governance with FICO DecisionOps and Xpress 10.0

Speakers: Carolyn Mooney, Bruno Vieira, Michael Perregaard, Carlos Zetina, Alexander Biele & Rusty Burlingame

Description

Generative AI has enabled us to write optimization models faster than ever. However, faster authorship hasn’t translated into faster business value.

This session examines how FICO is closing that gap with Xpress, its MI(NL)P solver for CPU and GPU workloads; and DecisionOps (formerly Nextmv), the platform for managing, testing, and operationalizing Gen-AI co-authored decision models powered by the tech you choose—whether that’s open-source or commercial optimization solvers, heuristics, rule engines, or simulation packages.

We’ll show the latest in FICO technology, improvements in MI(NL)P solves, GPU-accelerated optimization, and unified model management with DecisionOps. Customers will demonstrate how they leverage FICO’s Decision Intelligence software to drive measurable business outcomes. The session closes with practical references, training resources, and our Gen-AI assistants for teams ready to close their own authorship-to-value gap.

Open Tools and Standards for the Chance Economy

Speaker: Sam Savage

Description
The Open SIPmath™ Standard for Coherent Stochastic Data cures The Flaw of Averages with auditable data that obey both the laws of probability and the laws of arithmetic.

Discussing Chance without triggering Post-Traumatic Statistics Disorder (PTSD).

Prompting AI with SIP Libraries to create ChanceOmeters.

Using the open-source ChanceCalc add-in to create interactive simulations in Excel that DON’T REQUIRE THE ADD-IN TO RUN.

Prompting AI to create SIPmath 3.0 libraries that express up to 100 million Monte Carlo trials in 88 bytes without violating information theory.

See also OR/MS Today: Sept. 8, 2026, and June 23, 2026.

Littlefield 2.0: A Factory Management Simulation for Teaching Operations Management

Speaker: Samuel C. Wood

Description

Littlefield Operations is a competitive online simulation of either a factory or a medical laboratory that has been used to teach operations to more than half a million students in 500+ universities in 60+ countries. Instructors use the simulation as one or more graded assignments to engage and excite students studying topics like process analysis and inventory control. This presentation will introduce Littlefield 2.0 and allow participants to play a very fast and challenging scenario in the new student interface. Participants are encouraged but not required to bring a laptop or tablet to play the game.