{"id":1272,"date":"2025-03-25T14:44:58","date_gmt":"2025-03-25T19:44:58","guid":{"rendered":"https:\/\/meetings.informs.org\/wordpress\/annual2025\/?page_id=1272"},"modified":"2025-10-14T15:02:42","modified_gmt":"2025-10-14T20:02:42","slug":"technology-showcases","status":"publish","type":"page","link":"https:\/\/meetings.informs.org\/wordpress\/annual2025\/technology-showcases\/","title":{"rendered":"Technology Showcases"},"content":{"rendered":"\n
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Join the conference exhibitors as they discuss innovations and best practices in the field.\u00a0Technology Showcase presentations are educational (not commercial) and feature case studies which may include use of exhibitor products and services.\u00a0<\/p>\n

Professional Development Units (PDUs) are available to those who attend these sessions. All full conference registrants are welcome to join during the scheduled time.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Monday, October 27<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 8-8:35am
<\/strong>Location: A301<\/span><\/strong><\/p> <\/div>\n<\/div>\n <\/div>\n

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Beyond the Hype: Rethinking Text Analysis in the Age of Generative AI<\/h3>\n

Presented by:\u00a0Normand P\u00e9ladeau<\/strong><\/p>\n

In this presentation, we will explore latest advancements in generative AI and large language models (LLMs) and see their contribution as well as limitations for text analytics applications. While the excitement surrounding such new technologies is undeniable, older techniques still provide significant value and may even outperform newer methods in certain contexts. By critically examining the strengths and limitations of both established and cutting-edge approaches, we want to offer a balanced, realistic perspective on the role of recent developments in NLP and AI.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 8:40-9:15am<\/strong>
Location: A301
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Model and Solve Nonlinear Optimization Problems with
Artelys Knitro<\/h3>\n

Presented by: Richard Waltz<\/strong><\/p>\n

Artelys Knitro is the leading\u00a0solver 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\u00a0will 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, focusing on practical examples.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 11-11:35am
<\/strong>Location: A301<\/span><\/strong><\/p> <\/div>\n<\/div>\n <\/div>\n

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Building Trust in Optimization\u200b<\/h3>\n

Presented by:\u00a0Caroline Weinberg<\/strong>\u200b<\/p>\n

In this session\u00a0we will\u00a0explore some of\u00a0Gurobi’s\u00a0advanced features through the lens of\u00a0solution explainability, including solution pools, infeasibility analysis, and multi-scenario analysis.\u00a0\u00a0 Explainability in practice requires both technical skills and\u00a0successful communication with stakeholders who\u00a0don’t\u00a0know how\u00a0Gurobi\u00a0works (and\u00a0that’s ok!).\u00a0 We show how these tools\u00a0are not\u00a0just for modeling – they can help users\u00a0interpret optimization results and build trust their solutions.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 11:40am-12:15pm<\/strong>
Location: A301<\/span><\/strong><\/p> <\/div>\n<\/div>\n <\/div>\n

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Using an online factory management simulation to teach Operations Management<\/h3>\n

Presented by: Sam Wood<\/strong><\/p>\n

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Littlefield for Operations is a competitive online simulation of either a factory or a medical laboratory that has been used by more than half a million students in 500+ universities in 60+ countries over the past 26 years. In this session, we will discuss how professors use the newest version of Littlefield for Operations (2.0) to effectively teach foundational operations management topics such as process analysis, capacity planning and inventory control to students at various levels in various course formats.<\/p>\n<\/div> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 1:15\u20131:50pm<\/strong>
Location: A301<\/strong>
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Reducing Time-to-Value with FICO Xpress optimization suite
and gen ai<\/h3>\n

Presented by: Carlos Zetina and Rusty Burlingame<\/strong><\/p>\n

Time to Value measures how long it takes for technology projects to begin providing business value. Three critical milestones to achieve this are model creation, validation, and deployment. In this showcase, we’ll show how FICO Xpress Optimization Suite shortens Time to Value and supercharges Return on Investment (ROI) by providing a unified platform for development, validation, and deployment. We’ll show how FICO’s suite of products and Gen AI come together to turbocharge building and adoption of enterprise optimization applications deployable on any tech stack, be it server-less or via virtual machines, hosted on any cloud provider or on-premises infrastructure.<\/p>\n

Hear from Rusty Burlingame from Southwest Airlines, on how Southwest is using Xpress to improve customer experience, enhance employee engagement, and streamline operations to maximize revenue and support growth.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 1:55-2:30pm
<\/strong>Location: A301<\/span><\/strong><\/p> <\/div>\n<\/div>\n <\/div>\n

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Cracking the Vault with\u00a0Gurobot: Generative AI and the Future of Mathematical Modeling\u200b<\/h3>\n

Presented by: Cara Touretzky<\/strong><\/p>\n

Discover how\u00a0Gurobi\u00a0is exploring the use of generative AI to support and streamline the\u00a0modeling of mathematical optimization problems. Through the lens of a hands-on museum\u00a0heist challenge, we\u2019ll walk through examples of AI-assisted modeling across varying levels of\u00a0complexity. We\u2019ll highlight current capabilities, acknowledge present limitations, and offer a\u00a0glimpse into where we\u2019re headed next as we expand the role of AI in the modeling workflow.\u200b<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 2:45-3:20pm
<\/strong>Location: A301<\/strong><\/p> <\/div>\n<\/div>\n <\/div>\n

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DecisionOps in the Analytics Process: Collaboration, observability, testing, ecosystem, and workflows<\/h3>\n

Presented by: Carolyn Mooney and Tiffany Bogich<\/strong><\/p>\n

Optimization is founded upon the promise of efficiency and improving solutions. In today\u2019s analytics environment, the leading data science and optimization teams will be defined by how they apply DecisionOps practices to test, deploy, and operate these solutions alongside software and business stakeholders.<\/p>\n

Join this session to learn basic concepts, real-world applications, and how to get started with DecisionOps in Nextmv, a platform for accelerating decision model development. This session is relevant to anyone working with tools such as: OR-Tools, Pyomo, HiGHS, VROOM, Gurobi, AMPL, FICO Xpress, Hexaly, Jupyter Notebooks, Statsmodels, Prophet, scikit-learn, Databricks, Snowflake, and more.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 3:25-4pm
<\/strong>Location: A301<\/strong><\/p> <\/div>\n<\/div>\n <\/div>\n

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Computing Dual Bounds of Set-based Models Using Column Generation and Column Elimination in Hexaly<\/h3>\n

Presented by: Julien Darlay<\/strong><\/p>\n

Hexaly is a model-and-run solver that integrates heuristics and exact methods. A set-based modeling formalism was introduced to simplify the modeling of some combinatorial problems, like routing or packing problems. For instance, in a routing problem, list variables can be used to model the sequence of visits made by each truck. These decision variables are well suited for a heuristic search but are much more challenging to integrate into a mathematical programming approach to compute lower bounds. A direct MILP reformulation introduces a quadratic number of binary decisions with several big M constraints, leading to poor scalability and bounds. Hexaly automatically detects such structures in a user model and reformulates them in an extended MILP model to compute lower bounds parallel to a heuristic search. This model is solved efficiently using the literature’s state-of-the-art branch-and-cut-and-price techniques and column elimination algorithms. This talk will present the general approach, the algorithms used for the resolution, and some benchmarks on the classical vehicle routing and packing problems.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 4:15-4:50pm
<\/strong>Location: A301<\/strong><\/p> <\/div>\n<\/div>\n <\/div>\n

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At the intersection of AI, Data, and Advanced Materials
and Manufacturing<\/h3>\n

Presented by: Changchun (Chad) Zeng<\/strong><\/p>\n

This presentation overviews the diverse research in the Department of Industrial and Manufacturing Engineering (IME). We have an outstanding group of faculty members working in the areas vital to the national interest and to the betterment of society, i.e., advanced materials and manufacturing, nanomaterials and nanotechnology, smart materials, data science and analytics, artificial intelligence, machine learning and deep learning, systems engineering, transportation systems and supply chain logistics. Our faculty members are involved in these exciting areas on projects sponsored by prestigious funding agencies, i.e., NSF, NIH, DOE, DOD, NASA, AFRL, ONR, to name a few.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 4:55-5:30pm
<\/strong>Location: A301<\/strong><\/p> <\/div>\n<\/div>\n <\/div>\n

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Optimization Solution Development and Deployment: A Framework for Success<\/h3>\n

Presented by: Irv Lustig<\/strong><\/p>\n

For over 44 years, Princeton Consultants has developed and deployed numerous applications that leverage optimization to make better decisions for our clients. We have developed a set of best practices over that time that are also reflected in the recently published INFORMS Analytics Framework (IAF), for which Irv was a key contributor. The IAF provides a roadmap for successful analytics projects, including optimization, and contains specific tasks related to risk management. Irv will describe both the IAF and the Princeton 20, a set of 10 environmental and 10 technical risks to be evaluated at the commencement of any project. Understanding these risks in the context of the framework leads to best practices that improve the chances of success for your next optimization project.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Tuesday, October 28<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 8-8:35am<\/strong>
Location: A302<\/strong>
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Democratizing Digital Twins: From Real-Time Operations to Strategic Planning<\/h3>\n

Presented by: Andrew Siprelle<\/strong><\/p>\n

Digital twins serve different problem domains requiring different technical approaches. Traditional 3D kinematic simulation excels at spatial problems. Strategic capital investment decisions require different capabilities: rapid scenario analysis, statistical validation, and system interdependency revelation. This session presents a case study demonstrating time-compressed discrete event simulation methodology delivering strategic intelligence through rapid construction and statistical parameterization from historian data. The case reveals a critical insight: two equipment problems with similar historical downtime losses deliver 1.3x versus 5x actual gains when fixed. This gap illustrates why traditional loss analysis misleads prioritization decisions. The methodology enables Fortune 500-standard predictive modeling to become accessible.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 8-8:35am<\/strong>
Location: A301<\/strong>
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Advancing Decision Intelligence with AI-Assisted Simulation: Case Studies from the Strategic Decision Lab<\/h3>\n

Presented by: Alton Alexander<\/strong><\/p>\n

See how systems thinking and AI-assisted simulation can accelerate decision-making in education and practice. Through case studies in workforce scheduling, healthcare capacity, supply chains, and training pipelines, we show how the Strategic Decision Lab enables participants to design, calibrate, and compare scenarios rapidly. Attendees will see how AI assistants support model building, scenario exploration, and insight generation while maintaining transparency and rigor. Participants will gain practical methods to integrate AI-assisted simulation into their teaching or professional practice, learning how to enrich curricula, engage learners, and apply collaborative systems thinking for real-world decision support.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 8:40-9:15am<\/strong>
Location: A301<\/strong>
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Reducing Time-to-Value with FICO Xpress Optimization Suite
and Gen AI<\/h3>\n

Presented by: Carlos Zetina and Rusty Burlingame<\/strong><\/p>\n

Time to Value measures how long it takes for technology projects to begin providing business value. Three critical milestones to achieve this are model creation, validation, and deployment.<\/p>\n

In this talk, we\u2019ll show how FICO Xpress Optimization Suite shortens Time to Value and supercharges Return on Investment (ROI) by providing a unified platform for development, validation, and deployment.\u00a0 We\u2019ll show how FICO\u2019s suite of products and Gen AI come
together to turbocharge building and adoption of enterprise optimization applications
deployable on any tech stack, be it serverless or via virtual machines, hosted on any cloud
provider or on-premises infrastructure.<\/p>\n

Hear from Rusty Burlingame from Southwest Airlines, on how Southwest is using Xpress to improve customer experience, enhance employee engagement, and streamline operations to maximize revenue and support growth.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 8:40-9:15am<\/strong>
Location: A302<\/span><\/strong><\/p> <\/div>\n<\/div>\n <\/div>\n

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An Introduction to Modeling with GAMSPy<\/h3>\n

Presented by: Adam Christensen and Steven Dirkse<\/strong><\/p>\n

Our showcase offers a hands-on introduction to GAMSPy. GAMSPy combines the high-performance GAMS execution system with the flexible Python language, creating a powerful mathematical optimization package. It acts as a bridge between the expressive Python language and the robust GAMS system, allowing you to effortlessly create complex mathematical models and applications.<\/p>\n

Join us to explore GAMSPy’s fundamental functionalities through practical, interactive exercises. We’ll cover everything from defining sets, parameters, variables, and equations to solving models and retrieving results, all within a familiar Python environment. Beyond the basics, we’ll also provide a glimpse into more advanced features, demonstrating how GAMSPy can streamline complex modeling workflows and enhance your analytical capabilities.<\/p>\n

Whether you’re a seasoned GAMS user looking to integrate with Python or a Python user curious about optimization, this workshop will equip you with essential skills needed to get started and demonstrate what is possible with GAMSPy.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 11-11:35am
<\/strong>Location: A302<\/span><\/strong><\/p> <\/div>\n<\/div>\n <\/div>\n

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Solverminds\u2019 Scalable Optimization-as-a-Service<\/h3>\n

Presented by: Mukund Sharma & Valentin Weber<\/strong><\/p>\n

Explore how Solverminds is redefining optimization through client-centric, co-developed solutions. This session highlights use cases across various scheduling challenges, demonstrating real-time decision support, fuel optimization, and scheduling efficiency across the maritime and transport industries.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time:\u00a0<\/strong>11-11:35am<\/strong>
<\/strong>Location: A301<\/span><\/strong><\/p> <\/div>\n<\/div>\n <\/div>\n

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AI-Augmented Monte Carlo Simulation for Capital Investment Decisions in Innovation Project Portfolios<\/h3>\n

Presented by: Gustavo Vineuza<\/strong><\/p>\n

Capital investment decisions in innovation project portfolios are characterized by high uncertainty\u2014ranging from technical feasibility and development timelines to market adoption and regulatory approval. Traditional deterministic models often fail to capture these uncertainties, leading to suboptimal capital allocation and increased risk exposure. This paper introduces a decision-support framework that combines Monte Carlo Simulation (MCS) with artificial intelligence (AI) to support more robust, data-informed investment strategies.<\/p>\n

Monte Carlo Simulation is used to model uncertainty across financial and scheduling dimensions, producing probabilistic estimates for key metrics such as Net Present Value (NPV), Internal Rate of Return (IRR), and the likelihood of cost and time overruns. To improve simulation fidelity, AI techniques\u2014particularly machine learning\u2014are applied to historical and contextual project data. These models help refine input distributions, detect interdependencies between projects, and dynamically adjust assumptions in response to new evidence.<\/p>\n

Beyond input calibration, AI is used to support optimization efforts by analyzing simulated outcomes and identifying portfolio strategies that maximize expected value under defined risk constraints. This enables decision-makers to explore trade-offs between risk and return, better allocate limited capital, and gain visibility into the impact of uncertainty drivers.<\/p>\n

The proposed framework is demonstrated through a fictitious innovation portfolio composed of diverse early-stage projects. Results show improved transparency, better risk-adjusted returns, and actionable insights for capital allocation under uncertainty. The methodology is applicable to industries where innovation drives value, such as pharmaceuticals, energy, and technology.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 11:40am-12:15pm<\/strong>
Location: A301<\/span><\/strong><\/p> <\/div>\n<\/div>\n <\/div>\n

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From Classroom to Industry: Modern Optimization with AMPL for Energy, Finance, Supply Chain, and Beyond<\/h3>\n

Presented by: Gleb Belov & Marcos Dominguez Velad\u00a0<\/strong><\/p>\n

Optimization has never been more critical – or more accessible. This talk will show how students and applied researchers can bridge the gap between academic learning and real-world impact using AMPL in modern workflows. With free academic licenses now including commercial-grade access to leading linear solvers (Gurobi, CPLEX, Xpress, Mosek, COPT, HiGHS and more), AMPL offers an unmatched opportunity to develop and apply optimization skills directly in industry contexts.<\/p>\n

We will explore how AMPL integrates seamlessly with the tools you already know – Python, R, Jupyter, Colab, VS Code, cloud platforms, and modern data pipelines – making it a “set it and forget it” system for building models that stay faithful to the real problems you\u2019re solving. Attendees will see how AMPL powers large-scale, mission-critical applications in energy, finance, transportation, and supply chain, enabling companies to save costs, increase efficiency, and improve decision-making.<\/p>\n

By combining intuitive modeling with cutting-edge solver technology, AMPL empowers students and researchers not just to learn optimization, but to contribute immediately to high-impact, industry-grade projects. Join us to discover how AMPL can position you, or your students, at the forefront of applied optimization.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 11:40am-12:15pm
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Solverminds\u2019 Innovation in Progress: Optimization for
the Future<\/h3>\n

Presented by: Mohit Oberoi & Senthil Kumar<\/strong><\/p>\n

This session offers a forward-looking perspective on how Solverminds is developing next-generation optimization solutions. We\u2019ll share key concepts, and early-stage innovations from ongoing projects, showcasing how our evolving approach can be applied across shipping, logistics,\u00a0and broader transport ecosystems.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 1:15\u20131:50pm<\/strong>
Location: A301<\/span><\/strong><\/p> <\/div>\n<\/div>\n <\/div>\n

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Bayesian Optimization for Efficient Decision-Making in
Complex Systems<\/span><\/h3>\n

Presented by: Ross Metusalem<\/strong><\/p>\n

Bayesian Optimization (BO) is a sequential learning method for efficiently optimizing noisy, black-box, or expensive-to-evaluate functions. Starting with a small set of observations, BO fits a flexible probabilistic model to the data and uses that model to determine the next observation(s) to collect. Iterating on this process, BO balances exploration of uncertain areas of the factor space with exploitation of potential optima to arrive at a globally optimal solution. This session will establish the foundational concepts underlying BO and present a case study of BO in action.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time:\u00a0<\/strong>1:55-2:30pm
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Optimization Education with\u00a0Gurobi: A Social-Impact Case Study\u200b<\/h3>\n

Presented by: Lindsay Montanari & Everett Dutton<\/strong><\/p>\n

Gurobi, in partnership with ESUPS (Emergency Supply Pre-positioning Strategy), presents a new educational case study\u00a0showcasing ESUPS’ utilization of optimization to stage relief inventory for humanitarian organizations.\u200b \u00a0ESUPS unites NGOs, UN agencies, governments, and academics to improve logistics preparedness. The STOCKHOLM\u00a0platform (STOCK of Humanitarian Organizations Logistics Mapping) applies data analytics techniques including\u00a0optimization to determine where to pre-position supplies, minimize response times, and maximize coverage in crises\u00a0where every hour matters.\u200b<\/p>\n

This case study guides students and instructors through the full optimization pipeline: translating a complex\u00a0humanitarian challenge into data, math, and models that support real-world decision making. \u200bFreely available, it gives learners hands-on experience with optimization in action, demonstrating how these methods\u00a0can transform disaster response and deliver measurable social impact.\u200b<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 2:45-3:20pm
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Unlocking Full Optimization Potential with COPT<\/h3>\n

Presented by: Tiancheng Zhang<\/strong><\/p>\n

In this presentation, the COPT team will demonstrates new capabilities and functionalities introduced in the latest COPT release, including features like the nonlinear solver and GPU acceleration. Additionally, the speaker will share COPT’s advanced features and performance through live notebook demos, showcasing real-world use cases such as drone trajectory optimization, portfolio optimization and beyond.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 3:25-4pm
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LogixEdu: A Game-Based, Experiential Approach to Supply
Chain Learning<\/h3>\n

Presented by: Ziping Wang<\/strong><\/p>\n

LogixEdu transforms supply chain education through an interactive game that simulates the full journey from materials to manufacturing, distribution, and sales. By combining experiential learning with game-based design, it simplifies complex dynamics while fostering transferable skills such as adaptability, initiative, and teamwork. This innovation bridges classroom theory with industry practice, preparing students and professionals for real-world supply chain challenges in an engaging and accessible way.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 4:15-4:50pm
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Building and Solving Optimization Models with SAS<\/h3>\n

Presented by: Rob Pratt<\/strong><\/p>\n

SAS offers extensive analytic capabilities, including machine learning, deep learning, natural language processing, statistical analysis, optimization, and simulation. SAS analytic functionality is also available through the open, cloud-enabled design of SAS\u00ae Viya\u00ae. You can program in SAS or in other languages \u2013 Python, Lua, Java, and R.

OPTMODEL from SAS provides a powerful and intuitive algebraic optimization modeling language and unified support for building and solving LP, MILP, QP, conic, NLP, constraint programming, network-oriented, and black-box models. This showcase will include an overview of the optimization capabilities and demonstrate recently added features.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Wednesday, October 29<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 9:30-10:05am
<\/strong>Location: A301<\/span><\/strong><\/p> <\/div>\n<\/div>\n <\/div>\n

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Data Strategy Professionals<\/strong><\/p>\n

Business Value of AI Governance Frameworks<\/h3>\n

Presented by: Nicole Janeway Bills<\/strong><\/p>\n

The talk addresses critical knowledge gaps that many data practitioners face in navigating AI Governance.\u00a0 The presentation will provide insights into the strengths and weaknesses of various AI Governance frameworks from organizations such as NIST and OECD and companies such as Microsoft, AWS, and Google.\u00a0 Moreover, we’ll discuss practical recommendations for the application of these frameworks to mitigate risk and enhance business value.\u00a0<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n

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Time: 10:10-10:45am
<\/strong>Location: A301<\/span><\/strong><\/p> <\/div>\n<\/div>\n <\/div>\n

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VRP: when Research meets Reality<\/h3>\n

Presented by: Geoffrey De Smet<\/strong><\/p>\n

It\u2019s one thing to solve a VRPTW (Vehicle Routing Problem with Time Windows). It\u2019s another to put it in production for a fleet of 50,000 technicians and save hundreds of millions of dollars per year. It\u2019s not just more constraints\/objectives and more data.<\/p>\n

In this session, we will talk about the business and technical challenges of transforming an academic VRP into a solution that works well in production.<\/p> <\/div>\n<\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n","protected":false},"excerpt":{"rendered":"

Join the conference exhibitors as they discuss innovations and best practices in the field.\u00a0Technology Showcase presentations are educational (not commercial) and feature case studies which may include use of exhibitor products and services.\u00a0 Professional Development Units (PDUs) are available to those who attend these sessions. All full conference registrants are welcome to join during the […]<\/p>\n","protected":false},"author":46,"featured_media":4818,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"class_list":["post-1272","page","type-page","status-publish","has-post-thumbnail","hentry","has-post-title","has-post-date","has-post-category","has-post-tag","has-post-comment","has-post-author",""],"acf":[],"yoast_head":"\nTechnology Showcases - 2025 INFORMS Annual Meeting<\/title>\n<meta name=\"description\" content=\"Join our conference exhibitors as they discuss innovations and best practices in the field. Professional Development Units (PDUs) are available to those who attend these sessions. All attendees are welcome to join during the scheduled time.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/meetings.informs.org\/wordpress\/annual2025\/technology-showcases\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Technology Showcases\" \/>\n<meta property=\"og:description\" content=\"Join our conference exhibitors as they discuss innovations and best practices in the field. Professional Development Units (PDUs) are available to those who attend these sessions. 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All full conference registrants are welcome to join during the scheduled time.<\/p>\n<p>Monday, October 27<\/p>\n<p><strong>Time: 8-8:35am<br><\/strong><strong style=\"background-color: initial\">Location: A301<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/annual\/files\/2025\/08\/Provalis_Research_logo.png\" width=\"250\" height=\"110\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>Beyond the Hype: Rethinking Text Analysis in the Age of Generative AI<\/h3> <p><strong>Presented by:\u00a0Normand P\u00e9ladeau<\/strong><\/p> <p>In this presentation, we will explore latest advancements in generative AI and large language models (LLMs) and see their contribution as well as limitations for text analytics applications. While the excitement surrounding such new technologies is undeniable, older techniques still provide significant value and may even outperform newer methods in certain contexts. By critically examining the strengths and limitations of both established and cutting-edge approaches, we want to offer a balanced, realistic perspective on the role of recent developments in NLP and AI.<\/p>\n<p><strong>Time: 8:40-9:15am<\/strong><br><strong>Location: A301<br><\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/phoenix2023\/files\/2023\/09\/Arteyls2.png\" width=\"250\" height=\"90\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>Model and Solve Nonlinear Optimization Problems with <br>Artelys Knitro<\/h3> <p><strong>Presented by: Richard Waltz<\/strong><\/p> <p>Artelys Knitro is the leading\u00a0solver 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\u00a0will 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, focusing on practical examples.<\/p>\n<p><strong>Time: 11-11:35am<br><\/strong><strong style=\"background-color: initial\">Location: A301<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/phoenix2023\/files\/2023\/07\/Gurobi-Logo2.png\" width=\"250\" height=\"66\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>Building Trust in Optimization\u200b<\/h3> <p><strong>Presented by:\u00a0Caroline Weinberg<\/strong>\u200b<\/p> <p>In this session\u00a0we will\u00a0explore some of\u00a0Gurobi's\u00a0advanced features through the lens of\u00a0solution explainability, including solution pools, infeasibility analysis, and multi-scenario analysis.\u00a0\u00a0 Explainability in practice requires both technical skills and\u00a0successful communication with stakeholders who\u00a0don't\u00a0know how\u00a0Gurobi\u00a0works (and\u00a0that's ok!).\u00a0 We show how these tools\u00a0are not\u00a0just for modeling - they can help users\u00a0interpret optimization results and build trust their solutions.<\/p>\n<p><strong>Time: 11:40am-12:15pm<\/strong><br><strong>Location: A301<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/phoenix2023\/files\/2023\/06\/exhibitor-logo-responsive-learning-technologies.png\" width=\"250\" height=\"86\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>Using an online factory management simulation to teach Operations Management<\/h3> <p><strong>Presented by: Sam Wood<\/strong><\/p>\n<p>Littlefield for Operations is a competitive online simulation of either a factory or a medical laboratory that has been used by more than half a million students in 500+ universities in 60+ countries over the past 26 years. In this session, we will discuss how professors use the newest version of Littlefield for Operations (2.0) to effectively teach foundational operations management topics such as process analysis, capacity planning and inventory control to students at various levels in various course formats.<\/p>\n<p><strong>Time: 1:15\u20131:50pm<\/strong><br><strong>Location: A301<\/strong><br><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/seattle2024\/files\/2024\/07\/FICO-Logo.png\" width=\"300\" height=\"80\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>Reducing Time-to-Value with FICO Xpress optimization suite <br>and gen ai<\/h3> <p><strong>Presented by: Carlos Zetina and Rusty Burlingame<\/strong><\/p> <p>Time to Value measures how long it takes for technology projects to begin providing business value. Three critical milestones to achieve this are model creation, validation, and deployment. In this showcase, we'll show how FICO Xpress Optimization Suite shortens Time to Value and supercharges Return on Investment (ROI) by providing a unified platform for development, validation, and deployment. We'll show how FICO's suite of products and Gen AI come together to turbocharge building and adoption of enterprise optimization applications deployable on any tech stack, be it server-less or via virtual machines, hosted on any cloud provider or on-premises infrastructure.<\/p> <p>Hear from Rusty Burlingame from Southwest Airlines, on how Southwest is using Xpress to improve customer experience, enhance employee engagement, and streamline operations to maximize revenue and support growth.<\/p>\n<p><strong>Time: 1:55-2:30pm<br><\/strong><strong style=\"background-color: initial\">Location: A301<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/phoenix2023\/files\/2023\/07\/Gurobi-Logo2.png\" width=\"250\" height=\"66\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>Cracking the Vault with\u00a0Gurobot: Generative AI and the Future of Mathematical Modeling\u200b<\/h3> <p><strong>Presented by: Cara Touretzky<\/strong><\/p> <p>Discover how\u00a0Gurobi\u00a0is exploring the use of generative AI to support and streamline the\u00a0modeling of mathematical optimization problems. Through the lens of a hands-on museum\u00a0heist challenge, we\u2019ll walk through examples of AI-assisted modeling across varying levels of\u00a0complexity. We\u2019ll highlight current capabilities, acknowledge present limitations, and offer a\u00a0glimpse into where we\u2019re headed next as we expand the role of AI in the modeling workflow.\u200b<\/p>\n<p><strong>Time: 2:45-3:20pm<br><\/strong><strong style=\"background-color: initial\">Location: A301<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/phoenix2023\/files\/2023\/07\/web_ready_company_logo-nextmv-logo-horizontal-color.png\" width=\"250\" height=\"63\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>DecisionOps in the Analytics Process: Collaboration, observability, testing, ecosystem, and workflows<\/h3> <p><strong>Presented by: Carolyn Mooney and Tiffany Bogich<\/strong><\/p> <p>Optimization is founded upon the promise of efficiency and improving solutions. In today\u2019s analytics environment, the leading data science and optimization teams will be defined by how they apply DecisionOps practices to test, deploy, and operate these solutions alongside software and business stakeholders.<\/p> <p>Join this session to learn basic concepts, real-world applications, and how to get started with DecisionOps in Nextmv, a platform for accelerating decision model development. This session is relevant to anyone working with tools such as: OR-Tools, Pyomo, HiGHS, VROOM, Gurobi, AMPL, FICO Xpress, Hexaly, Jupyter Notebooks, Statsmodels, Prophet, scikit-learn, Databricks, Snowflake, and more.<\/p>\n<p><strong>Time: 3:25-4pm<br><\/strong><strong style=\"background-color: initial\">Location: A301<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/annual\/files\/2025\/04\/hexaly-orange.svg\" width=\"250\" height=\"81\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>Computing Dual Bounds of Set-based Models Using Column Generation and Column Elimination in Hexaly<\/h3> <p><strong>Presented by: Julien Darlay<\/strong><\/p> <p>Hexaly is a model-and-run solver that integrates heuristics and exact methods. A set-based modeling formalism was introduced to simplify the modeling of some combinatorial problems, like routing or packing problems. For instance, in a routing problem, list variables can be used to model the sequence of visits made by each truck. These decision variables are well suited for a heuristic search but are much more challenging to integrate into a mathematical programming approach to compute lower bounds. A direct MILP reformulation introduces a quadratic number of binary decisions with several big M constraints, leading to poor scalability and bounds. Hexaly automatically detects such structures in a user model and reformulates them in an extended MILP model to compute lower bounds parallel to a heuristic search. This model is solved efficiently using the literature's state-of-the-art branch-and-cut-and-price techniques and column elimination algorithms. This talk will present the general approach, the algorithms used for the resolution, and some benchmarks on the classical vehicle routing and packing problems.<\/p>\n<p><strong>Time: 4:15-4:50pm<br><\/strong><strong style=\"background-color: initial\">Location: A301<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/annual\/files\/2025\/07\/392658368-FAMU-FSU-company_logo-F2COE-St.png\" width=\"300\" height=\"80\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>At the intersection of AI, Data, and Advanced Materials <br>and Manufacturing<\/h3> <p><strong>Presented by: Changchun (Chad) Zeng<\/strong><\/p> <p>This presentation overviews the diverse research in the Department of Industrial and Manufacturing Engineering (IME). We have an outstanding group of faculty members working in the areas vital to the national interest and to the betterment of society, i.e., advanced materials and manufacturing, nanomaterials and nanotechnology, smart materials, data science and analytics, artificial intelligence, machine learning and deep learning, systems engineering, transportation systems and supply chain logistics. Our faculty members are involved in these exciting areas on projects sponsored by prestigious funding agencies, i.e., NSF, NIH, DOE, DOD, NASA, AFRL, ONR, to name a few.<\/p>\n<p><strong>Time: 4:55-5:30pm<br><\/strong><strong style=\"background-color: initial\">Location: A301<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/annual\/files\/2025\/09\/PCI-2024.logo_.NO-URL_300dpi_Transparent.png\" width=\"300\" height=\"91\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>Optimization Solution Development and Deployment: A Framework for Success<\/h3> <p><strong>Presented by: Irv Lustig<\/strong><\/p> <p>For over 44 years, Princeton Consultants has developed and deployed numerous applications that leverage optimization to make better decisions for our clients. We have developed a set of best practices over that time that are also reflected in the recently published INFORMS Analytics Framework (IAF), for which Irv was a key contributor. The IAF provides a roadmap for successful analytics projects, including optimization, and contains specific tasks related to risk management. Irv will describe both the IAF and the Princeton 20, a set of 10 environmental and 10 technical risks to be evaluated at the commencement of any project. Understanding these risks in the context of the framework leads to best practices that improve the chances of success for your next optimization project.<\/p>\n<p>Tuesday, October 28<\/p>\n<p><strong>Time: 8-8:35am<\/strong><br><strong>Location: A302<\/strong><br><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/annual\/files\/2025\/10\/ChiAha-web_ready_company_logo-Horizontal.jpg\" width=\"300\" height=\"146\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>Democratizing Digital Twins: From Real-Time Operations to Strategic Planning<\/h3> <p><strong>Presented by: Andrew Siprelle<\/strong><\/p> <p>Digital twins serve different problem domains requiring different technical approaches. Traditional 3D kinematic simulation excels at spatial problems. Strategic capital investment decisions require different capabilities: rapid scenario analysis, statistical validation, and system interdependency revelation. This session presents a case study demonstrating time-compressed discrete event simulation methodology delivering strategic intelligence through rapid construction and statistical parameterization from historian data. The case reveals a critical insight: two equipment problems with similar historical downtime losses deliver 1.3x versus 5x actual gains when fixed. This gap illustrates why traditional loss analysis misleads prioritization decisions. The methodology enables Fortune 500-standard predictive modeling to become accessible.<\/p>\n<p><strong>Time: 8-8:35am<\/strong><br><strong>Location: A301<\/strong><br><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/annual\/files\/2025\/09\/Veydra-logo.png\" width=\"300\" height=\"69\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>Advancing Decision Intelligence with AI-Assisted Simulation: Case Studies from the Strategic Decision Lab<\/h3> <p><strong>Presented by: Alton Alexander<\/strong><\/p> <p>See how systems thinking and AI-assisted simulation can accelerate decision-making in education and practice. Through case studies in workforce scheduling, healthcare capacity, supply chains, and training pipelines, we show how the Strategic Decision Lab enables participants to design, calibrate, and compare scenarios rapidly. Attendees will see how AI assistants support model building, scenario exploration, and insight generation while maintaining transparency and rigor. Participants will gain practical methods to integrate AI-assisted simulation into their teaching or professional practice, learning how to enrich curricula, engage learners, and apply collaborative systems thinking for real-world decision support.<\/p>\n<p><strong>Time: 8:40-9:15am<\/strong><br><strong>Location: A301<\/strong><br><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/seattle2024\/files\/2024\/07\/FICO-Logo.png\" width=\"300\" height=\"80\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>Reducing Time-to-Value with FICO Xpress Optimization Suite <br>and Gen AI<\/h3> <p><strong>Presented by: Carlos Zetina and Rusty Burlingame<\/strong><\/p> <p>Time to Value measures how long it takes for technology projects to begin providing business value. Three critical milestones to achieve this are model creation, validation, and deployment.<\/p> <p>In this talk, we\u2019ll show how FICO Xpress Optimization Suite shortens Time to Value and supercharges Return on Investment (ROI) by providing a unified platform for development, validation, and deployment.\u00a0 We\u2019ll show how FICO\u2019s suite of products and Gen AI come <br>together to turbocharge building and adoption of enterprise optimization applications <br>deployable on any tech stack, be it serverless or via virtual machines, hosted on any cloud <br>provider or on-premises infrastructure.<\/p> <p>Hear from Rusty Burlingame from Southwest Airlines, on how Southwest is using Xpress to improve customer experience, enhance employee engagement, and streamline operations to maximize revenue and support growth.<\/p>\n<p><strong>Time: 8:40-9:15am<\/strong><br><strong>Location: A302<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/phoenix2023\/files\/2023\/06\/GAMS_with-slogan.png\" width=\"250\" height=\"98\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>An Introduction to Modeling with GAMSPy<\/h3> <p><strong>Presented by: Adam Christensen and Steven Dirkse<\/strong><\/p> <p>Our showcase offers a hands-on introduction to GAMSPy. GAMSPy combines the high-performance GAMS execution system with the flexible Python language, creating a powerful mathematical optimization package. It acts as a bridge between the expressive Python language and the robust GAMS system, allowing you to effortlessly create complex mathematical models and applications.<\/p> <p>Join us to explore GAMSPy's fundamental functionalities through practical, interactive exercises. We'll cover everything from defining sets, parameters, variables, and equations to solving models and retrieving results, all within a familiar Python environment. Beyond the basics, we'll also provide a glimpse into more advanced features, demonstrating how GAMSPy can streamline complex modeling workflows and enhance your analytical capabilities.<\/p> <p>Whether you're a seasoned GAMS user looking to integrate with Python or a Python user curious about optimization, this workshop will equip you with essential skills needed to get started and demonstrate what is possible with GAMSPy.<\/p>\n<p><strong>Time: 11-11:35am<br><\/strong><strong style=\"background-color: initial\">Location: A302<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/annual\/files\/2025\/07\/SOLVERMINDS.png\" width=\"300\" height=\"50\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>Solverminds\u2019 Scalable Optimization-as-a-Service<\/h3> <p><strong>Presented by: Mukund Sharma & Valentin Weber<\/strong><\/p> <p>Explore how Solverminds is redefining optimization through client-centric, co-developed solutions. This session highlights use cases across various scheduling challenges, demonstrating real-time decision support, fuel optimization, and scheduling efficiency across the maritime and transport industries.<\/p>\n<p><strong>Time:\u00a0<\/strong><strong style=\"background-color: initial\">11-11:35am<\/strong><strong><br><\/strong><strong style=\"background-color: initial\">Location: A301<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/annual\/files\/2025\/10\/VS-FG-logos-cropped.jpg\" width=\"600\" height=\"108\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>AI-Augmented Monte Carlo Simulation for Capital Investment Decisions in Innovation Project Portfolios<\/h3> <p><strong>Presented by: Gustavo Vineuza<\/strong><\/p> <p>Capital investment decisions in innovation project portfolios are characterized by high uncertainty\u2014ranging from technical feasibility and development timelines to market adoption and regulatory approval. Traditional deterministic models often fail to capture these uncertainties, leading to suboptimal capital allocation and increased risk exposure. This paper introduces a decision-support framework that combines Monte Carlo Simulation (MCS) with artificial intelligence (AI) to support more robust, data-informed investment strategies.<\/p> <p>Monte Carlo Simulation is used to model uncertainty across financial and scheduling dimensions, producing probabilistic estimates for key metrics such as Net Present Value (NPV), Internal Rate of Return (IRR), and the likelihood of cost and time overruns. To improve simulation fidelity, AI techniques\u2014particularly machine learning\u2014are applied to historical and contextual project data. These models help refine input distributions, detect interdependencies between projects, and dynamically adjust assumptions in response to new evidence.<\/p> <p>Beyond input calibration, AI is used to support optimization efforts by analyzing simulated outcomes and identifying portfolio strategies that maximize expected value under defined risk constraints. This enables decision-makers to explore trade-offs between risk and return, better allocate limited capital, and gain visibility into the impact of uncertainty drivers.<\/p> <p>The proposed framework is demonstrated through a fictitious innovation portfolio composed of diverse early-stage projects. Results show improved transparency, better risk-adjusted returns, and actionable insights for capital allocation under uncertainty. The methodology is applicable to industries where innovation drives value, such as pharmaceuticals, energy, and technology.<\/p>\n<p><strong>Time: 11:40am-12:15pm<\/strong><br><strong>Location: A301<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/seattle2024\/files\/2024\/07\/AMPL-web_ready_company_logo.png\" width=\"300\" height=\"92\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>From Classroom to Industry: Modern Optimization with AMPL for Energy, Finance, Supply Chain, and Beyond<\/h3> <p><strong>Presented by: Gleb Belov & Marcos Dominguez Velad\u00a0<\/strong><\/p> <p>Optimization has never been more critical - or more accessible. This talk will show how students and applied researchers can bridge the gap between academic learning and real-world impact using AMPL in modern workflows. With free academic licenses now including commercial-grade access to leading linear solvers (Gurobi, CPLEX, Xpress, Mosek, COPT, HiGHS and more), AMPL offers an unmatched opportunity to develop and apply optimization skills directly in industry contexts.<\/p> <p>We will explore how AMPL integrates seamlessly with the tools you already know - Python, R, Jupyter, Colab, VS Code, cloud platforms, and modern data pipelines - making it a \"set it and forget it\" system for building models that stay faithful to the real problems you\u2019re solving. Attendees will see how AMPL powers large-scale, mission-critical applications in energy, finance, transportation, and supply chain, enabling companies to save costs, increase efficiency, and improve decision-making.<\/p> <p>By combining intuitive modeling with cutting-edge solver technology, AMPL empowers students and researchers not just to learn optimization, but to contribute immediately to high-impact, industry-grade projects. Join us to discover how AMPL can position you, or your students, at the forefront of applied optimization.<\/p>\n<p><strong>Time: 11:40am-12:15pm<br><\/strong><strong style=\"background-color: initial\">Location: A302<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/annual\/files\/2025\/07\/SOLVERMINDS.png\" width=\"300\" height=\"50\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>Solverminds\u2019 Innovation in Progress: Optimization for <br>the Future<\/h3> <p><strong>Presented by: Mohit Oberoi & Senthil Kumar<\/strong><\/p> <p>This session offers a forward-looking perspective on how Solverminds is developing next-generation optimization solutions. We\u2019ll share key concepts, and early-stage innovations from ongoing projects, showcasing how our evolving approach can be applied across shipping, logistics,\u00a0and broader transport ecosystems.<\/p>\n<p><strong>Time: 1:15\u20131:50pm<\/strong><br><strong>Location: A301<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/annual\/files\/2025\/08\/JMP-web_ready_company_logo.png\" width=\"300\" height=\"81\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>Bayesian Optimization for Efficient Decision-Making in<br>Complex Systems<\/h3> <p><strong>Presented by: Ross Metusalem<\/strong><\/p> <p>Bayesian Optimization (BO) is a sequential learning method for efficiently optimizing noisy, black-box, or expensive-to-evaluate functions. Starting with a small set of observations, BO fits a flexible probabilistic model to the data and uses that model to determine the next observation(s) to collect. Iterating on this process, BO balances exploration of uncertain areas of the factor space with exploitation of potential optima to arrive at a globally optimal solution. This session will establish the foundational concepts underlying BO and present a case study of BO in action.<\/p>\n<p><strong>Time:\u00a0<\/strong><strong style=\"background-color: initial\">1:55-2:30pm<br><\/strong><strong>Location: A301<\/strong><br><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/phoenix2023\/files\/2023\/07\/Gurobi-Logo2.png\" width=\"250\" height=\"66\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>Optimization Education with\u00a0Gurobi: A Social-Impact Case Study\u200b<\/h3> <p><strong>Presented by: Lindsay Montanari & Everett Dutton<\/strong><\/p> <p>Gurobi, in partnership with ESUPS (Emergency Supply Pre-positioning Strategy), presents a new educational case study\u00a0showcasing ESUPS' utilization of optimization to stage relief inventory for humanitarian organizations.\u200b \u00a0ESUPS unites NGOs, UN agencies, governments, and academics to improve logistics preparedness. The STOCKHOLM\u00a0platform (STOCK of Humanitarian Organizations Logistics Mapping) applies data analytics techniques including\u00a0optimization to determine where to pre-position supplies, minimize response times, and maximize coverage in crises\u00a0where every hour matters.\u200b<\/p> <p>This case study guides students and instructors through the full optimization pipeline: translating a complex\u00a0humanitarian challenge into data, math, and models that support real-world decision making. \u200bFreely available, it gives learners hands-on experience with optimization in action, demonstrating how these methods\u00a0can transform disaster response and deliver measurable social impact.\u200b<\/p>\n<p><strong>Time: 2:45-3:20pm<br><\/strong><strong style=\"background-color: initial\">Location: A301<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/annual\/files\/2023\/09\/copt_logo.png\" width=\"275\" height=\"97\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>Unlocking Full Optimization Potential with COPT<\/h3> <p><strong>Presented by: Tiancheng Zhang<\/strong><\/p> <p>In this presentation, the COPT team will demonstrates new capabilities and functionalities introduced in the latest COPT release, including features like the nonlinear solver and GPU acceleration. Additionally, the speaker will share COPT's advanced features and performance through live notebook demos, showcasing real-world use cases such as drone trajectory optimization, portfolio optimization and beyond.<\/p>\n<p><strong>Time: 3:25-4pm<br><\/strong><strong style=\"background-color: initial\">Location: A301<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/annual\/files\/2025\/10\/LogixEDU_logo-1.png\" width=\"175\" height=\"175\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>LogixEdu: A Game-Based, Experiential Approach to Supply <br>Chain Learning<\/h3> <p><strong>Presented by: Ziping Wang<\/strong><\/p> <p>LogixEdu transforms supply chain education through an interactive game that simulates the full journey from materials to manufacturing, distribution, and sales. By combining experiential learning with game-based design, it simplifies complex dynamics while fostering transferable skills such as adaptability, initiative, and teamwork. This innovation bridges classroom theory with industry practice, preparing students and professionals for real-world supply chain challenges in an engaging and accessible way.<\/p>\n<p><strong>Time: 4:15-4:50pm<br>Location: A301<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/annual\/files\/2025\/09\/sas-logo-blue.png\" width=\"275\" height=\"110\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>Building and Solving Optimization Models with SAS<\/h3> <p><strong>Presented by: Rob Pratt<\/strong><\/p> <p>SAS offers extensive analytic capabilities, including machine learning, deep learning, natural language processing, statistical analysis, optimization, and simulation. SAS analytic functionality is also available through the open, cloud-enabled design of SAS\u00ae Viya\u00ae. You can program in SAS or in other languages \u2013 Python, Lua, Java, and R. <br><br>OPTMODEL from SAS provides a powerful and intuitive algebraic optimization modeling language and unified support for building and solving LP, MILP, QP, conic, NLP, constraint programming, network-oriented, and black-box models. This showcase will include an overview of the optimization capabilities and demonstrate recently added features.<\/p>\n<p>Wednesday, October 29<\/p>\n<p><strong>Time: 9:30-10:05am<br><\/strong><strong style=\"background-color: initial\">Location: A301<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/annual\/files\/2025\/08\/DSP-logo_cdmp.webp\" width=\"120\" height=\"120\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<p style=\"text-align: center\"><strong>Data Strategy Professionals<\/strong><\/p> <h3>Business Value of AI Governance Frameworks<\/h3> <p><strong>Presented by: Nicole Janeway Bills<\/strong><\/p> <p>The talk addresses critical knowledge gaps that many data practitioners face in navigating AI Governance.\u00a0 The presentation will provide insights into the strengths and weaknesses of various AI Governance frameworks from organizations such as NIST and OECD and companies such as Microsoft, AWS, and Google.\u00a0 Moreover, we'll discuss practical recommendations for the application of these frameworks to mitigate risk and enhance business value.\u00a0<\/p>\n<p><strong>Time: 10:10-10:45am<br><\/strong><strong style=\"background-color: initial\">Location: A301<\/strong><\/p>\n<img src=\"https:\/\/meetings.informs.org\/wordpress\/annual\/files\/2025\/10\/timefoldai_logo.jpg\" width=\"150\" height=\"150\" title=\"Technology Showcases\" alt=\"Technology Showcases\">\n<h3>VRP: when Research meets Reality<\/h3> <p><strong>Presented by: Geoffrey De Smet<\/strong><\/p> <p>It\u2019s one thing to solve a VRPTW (Vehicle Routing Problem with Time Windows). It\u2019s another to put it in production for a fleet of 50,000 technicians and save hundreds of millions of dollars per year. It\u2019s not just more constraints\/objectives and more data.<\/p> <p>In this session, we will talk about the business and technical challenges of transforming an academic VRP into a solution that works well in production.<\/p>","_links":{"self":[{"href":"https:\/\/meetings.informs.org\/wordpress\/annual2025\/wp-json\/wp\/v2\/pages\/1272","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/meetings.informs.org\/wordpress\/annual2025\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/meetings.informs.org\/wordpress\/annual2025\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/meetings.informs.org\/wordpress\/annual2025\/wp-json\/wp\/v2\/users\/46"}],"replies":[{"embeddable":true,"href":"https:\/\/meetings.informs.org\/wordpress\/annual2025\/wp-json\/wp\/v2\/comments?post=1272"}],"version-history":[{"count":748,"href":"https:\/\/meetings.informs.org\/wordpress\/annual2025\/wp-json\/wp\/v2\/pages\/1272\/revisions"}],"predecessor-version":[{"id":10200,"href":"https:\/\/meetings.informs.org\/wordpress\/annual2025\/wp-json\/wp\/v2\/pages\/1272\/revisions\/10200"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/meetings.informs.org\/wordpress\/annual2025\/wp-json\/wp\/v2\/media\/4818"}],"wp:attachment":[{"href":"https:\/\/meetings.informs.org\/wordpress\/annual2025\/wp-json\/wp\/v2\/media?parent=1272"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}