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Technology Showcase

Take advantage of these showcases for a hands on demonstration of the latest in the industry. All attendees are welcome to join during the scheduled time or on demand following the conference. Descriptions Below

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Optimization Direct

ODH|CPLEX – An Optimizer For Hard MIPs &  A case study on solving Hard Redistricting problems

Date & Time: Sunday, October 24, 10-10:30am

Mixed Integer Programming Models (MIPs) commonly solved are becoming larger and more complex in response to much more readily available data and cheaper computer resources. ODH|CPLEX handles large models by co-running a set of heuristics within a traditional branch-and-cut optimizer so as to find good, usable solutions to problems that would otherwise be intractable. We outline the structural decomposition technology used and demonstrate its effectiveness on many user instances as well as its ability to find solutions to standard test models to which no solution has been previously known. We also present results from solving complex State Redistricting problems. 

Rockwell Automation

Rockwell Automation

Using Arena Simulation to Have Confidence in your Business Decisions

Presented by: Nancy Zupick, Manager Simulation, Consulting at Rockwell Automation
Date & Time: Sunday, October 24, 11-11:30am

The session will begin with what you need to know before starting a simulation project and some advice on how to keep your project on track and focused on your objectives. 

This presentation will include how Arena simulation is applied within business settings to assist in making decisions about labor management, process changes, capital improvements and various other situations that require a more thorough analysis before committing time and money to an effort.

MyEducator

This IS IT! Interactive Smart Textbooks for the Modern Program! 

Presented by: Jaret Wilson, Scotty Pectol
Date & Time: Sunday, October 24, 12noon-12:30pm

This is modern higher education! An affordable alternative to OER with up-to-date content from world-class author teams. Created by professors for professors, MyEducator smart interactive textbooks and learning resources are ideal for any classroom setting and work within live technology environments so your students don’t just learn, they do! Our approach enhances student engagement, improves learning outcomes, instructors receive better teaching evaluations, and students have more fun in the classroom. 

During this 30 minute presentation we’ll share how each smart learning resource, hosted on our intuitive platform, is filled with auto-graded assessments, ample instructor material, and robust analytics all with a seamless single sign-on LMS integration. Additionally, all our learning resources provide students an affordable price with lifetime access and best-in-class service. 

Full access will be given to any book on our platform to attendees. 

SAS logo

SAS

Medical Resource Optimization with SAS

Presented by: Natalia Summerville, Senior Manager, Advanced Analytics R&D, SAS, Subramanian Pazhani, Senior Operations Research Specialist, SAS
Date & Time: Monday, October 25, 9-9:30am

This technology showcase demonstrates a new medical resource optimization solution. SAS and Cleveland Clinic have collaborated to develop this solution to help medical organizations effectively manage their resources during the COVID-19 pandemic. After pausing non-emergency visits and elective procedures during the pandemic’s initial peak, Cleveland Clinic needed to decide how best to reopen their facilities and services. This solution generates a reopening plan that balances hospital economics, efficient use of resources, and patient access to quality clinical care across multiple locations and numerous medical services. The plan also accounts for the constraints imposed by ongoing COVID-19 testing requirements and test availability.

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DecisionBrain

Take your Optimization Model (CPLEX or others) to the Cloud with DBOS!

Presented by: Michel Eisenmann
Date & Time:
 Monday, October 25, 10-10:30am

DecisionBrain Optimization Server (DBOS) is specifically designed to help build and deploy fully scalable optimization-based applications. It enables optimization developers to focus on their models and help them effortlessly deploy those models in production in a context that will support multiple parallel runs on dedicated resources.

To achieve this, DBOS lets you encapsulate any computational module (optimization solvers, analytics modules, etc.) into so-called “Workers”. Workers can be deployed on dedicated resources (local, private, or public cloud) to ensure the best execution time. When deployed on Kubernetes, Workers may be activated on-demand to reduce cloud costs.

DBOS can be used in a stand-alone mode to run computations (for development purposes for example). It can also be integrated with existing applications to let them provide scalable and on-demand optimization capabilities as well as powerful monitoring capabilities.
 
In this presentation, we will demonstrate how this technology can be used to:

  • Encapsulate a Cplex model in a Worker
  • Deploy this Worker on a Kubernetes cluster using resources only on-demand
  • Monitor Real-time Executions

Speakers Bio:
Michel Eisenmann, Chief Technology Officer at DecisionBrain
Michel has 30 years of experience in the deployment of Optimization-based solutions for large organizations across the world. He initially worked at ILOG to build one of the first graphical object-oriented libraries. He then designed and lead the building of several platforms to facilitate and accelerate optimization solution deployments across multiple industries. After that, he worked as a Senior Solution Client Specialist for optimization solutions and as a member of the R&D Board for the IBM Decision Optimization Center product. He joined DecisionBrain in 2018 to head the development of the DBGene platform. He is now supervising all development efforts at DecisionBrain.

IBM logo

IBM

Radical simplification for the creation of optimization models

Presented by: Dharmashankar Subramanian (Principal Research Staff Member) & Segev Wasserkrug (STSM, Decision Optimization and Game Theory Research)
Date & Time: Monday, October 25, 11-11:30am

We will demonstrate a unique technology being developed by IBM to radically simplify and speed up the creation of optimization models. This is done through a combination of data driven and simplified modeling techniques, thereby also creating end-to-end data to decisions pipelines.

When you interact with IBM, this serves as your authorization to INFORMS or its vendor to provide your contact information to IBM in order for IBM to follow up on your interaction. IBM’s use of your contact information is governed by the IBM Privacy Policy 

simio

Simio

The Application of Simio Scheduling in Industry 4.0

Presented by: Eric Howard and Adam Sneath
Date & Time: Monday, October 25, 12noon-12:30pm

Simulation has traditionally been applied in system design projects where the basic objective is to evaluate alternatives and predict and improve the long term system performance. In this role, simulation has become a standard business tool with many documented success stories. Beyond these traditional system design applications, simulation can also play a powerful role in scheduling by predicting and improving the short term performance of a system. In the manufacturing context, the major new trend is towards digitally connected factories that introduce a number of unique requirements which traditional simulation tools do not address. Simio has been designed from the ground up with a focus on both traditional applications as well as advanced scheduling, with the basic idea that a single Simio model can serve both purposes. In this paper we will focus on the application of Simio simulation in the Industry 4.0 environment.

GAMS logo

GAMS

Turning Models Into Applications– GAMS Engine and GAMS Transfer

Presented by: Adam Christensen & Steven Dirkse
Date & Time:
 Monday, October 25, 1-1:30pm

The right tools help you deploy your GAMS model and maximize the impact of your decision support application. GAMS Engine is a powerful tool for solving GAMS models, either on-prem or in the cloud. Engine acts as a broker between applications or users with GAMS models to solve and the computational resources used for this task. Central to Engine is a modern REST API that provides an interface to a scalable Kubernetes-based system of services, providing API, database, queue, and a configurable number of GAMS workers. GAMS Transfer is an API (available in Python, Matlab, and soon R) that makes moving data between GAMS and your computational environment fast and easy. By leveraging open source data science tools such as Pandas/Numpy, GAMS Transfer is able to take advantage of a suite of useful (and platform independent) I/O tools to deposit data into GDX or withdraw GDX results to a number of data endpoints (i.e., visualizations, databases, etc.).

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Springer Nature

Title TBD

Date & Time: Tuesday October 26, 9-9:30 am

Details to come.

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Rochester Institute of Technology

Industrial Engineering Graduate Programs @ Rochester Institute of Technology

Date & Time: Tuesday October 26, 10-10:30 am

Come learn about pursuing a graduate degree in the Industrial and Systems Engineering Department at RIT. Our student focused department offers a PhD in Mechanical and Industrial Engineering and 3 MS degrees: MS Industrial and Systems Engineering, ME Engineering Management, and an MS in Sustainable Engineering. In this session we’ll provide some program highlights, discuss our faculty’s research interests, and detail what sets RIT apart from other schools. You’ll have plenty of time to ask questions about the application process, scholarship opportunities, and life as an RIT Tiger.

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LINDO Systems, Inc.

Optimization Modeling Made Easy

Presented by: Mark Wiley
Date & Time: Tuesday, October 26, 11-11:30am

See how exceptional ease of use, wide range of capabilities, and flexibility have made LINDO software the tool of choice for thousands of Operations Research professionals. LINDO offers solvers to cover all your optimization needs. The Linear Programming solvers handle million variable/constraint problems fast and reliably. The Quadratic/SOCP/Barrier solver efficiently handles quadratically constrained problems. The Integer solver works fast and reliably with LP, QP and NLP models. The Global NLP solver finds the guaranteed global optimum of nonconvex models. The Stochastic Programming solver has a full range of capabilities for planning under uncertainty.

Get an overview of our powerful modeling tools and find out about the newest enhancements and features.

  • What’sBest! is an add-in to Excel that you can use to quickly build models that managers can use and understand.
  • LINGO is a full featured modeling language for expressing complex models clearly and concisely. It has links to Excel and databases that make data I/O easy, plus programming capability and graphics.
gurobi_logo

Gurobi Optimization

New Enhancements in Gurobi 9.5

Presented by: Tobias Achterberg, VP of R&D, Gurobi Optimization
Date & Time: Tuesday, October 26, 12noon-12:30pm

In this technology showcase, Tobias Achterberg, VP of R&D at Gurobi Optimization, will give a sneak peek of the performance enhancements and new features in the upcoming release of Gurobi 9.5, the world’s most powerful mathematical optimization solver.

Bio:

Dr. Achterberg studied mathematics and computer science at the Technical University of Berlin and the Zuse Institute Berlin. He finished his PhD in mathematics under supervision of Prof. Martin Grötschel in 2007. Dr. Achterberg is the author of SCIP, currently the best academic MIP solver. In addition to numerous publications in scientific journals, he has also received several awards for his dissertation and for SCIP, such as the Beale-Orchard-Hays Prize. From 2006, Dr. Achterberg worked for ILOG/IBM as developer of CPLEX in versions 11 to 12.6. Since 2014 he has been involved as a Senior Developer in the development of the Gurobi Optimizer.

JMP-logo-color_600x150

JMP, a Division of SAS

Interactive Visualizations to Explore Data using JMP Statistical Software

Presented by: Kevin Potcner
Date & Time: Tuesday, October 26, 1-1:30pm

Exploring data – especially complex multi-dimensional data – can be daunting for students new to the statistical sciences. A focus on formal statistical techniques and explicit use of formulas often result in exposing students only to basic analysis problems (e.g., 1-sample inference, 2-sample comparisons, modeling with few explanatory variables, etc.).

The data that these students will be presented with once they enter the workforce will not be this simple. These datasets will contain a large number of variables and not fit the simple inferential techniques that is part of the standard statistics curriculum.

Using the JMP Statistical Software, the presenter will illustrate a variety of ideas on how to incorporate dynamic interactive visualization tools into your curriculum to help excite students learning the statistical sciences and better equip them to handle the types of data and problems they will face in their future jobs.

MathWorks logo

Mathworks

Title TBD

Date & Time: Wednesday, October 27, 9-9:30am

Details to come