Rapid Model Building for Better
Decisions During Uncertainty
Presented by: Gertjan de Lange, Product Owner
Wednesday, November 11, 1:05-1:35pm
This session will demonstrate how the combination of intuitive modeling and visualization tools in AIMMS enable you to easily test new approaches on the fly. You can go from idea to a prototype quickly and iterate with end-users, leading to higher adoption and satisfaction and significant value for your organization.
In 25 minutes, we will use a classic transportation optimization problem to demonstrate how easy it is to go from a problem statement to an interactive application you can share with peers and end users.
o See how simple it is to model sets, parameters, variables and constraints that defines your mathematical formulation
– Experience how easy it is to fill your model with data (and change it)
o Discover how the AIMMS IDE allows you to analyze a model and helps improve effective building and testing
– Learn how an interactive web application can be built on top of your model
– Learn to deploy a model on the AIMMS Cloud and add user rights to control who can use it
– See how an end user runs it from their browser device (no other software needed).
There are many other tools available in AIMMS which we don’t have time to cover in this session. For instance, diagnostic tools like the math program inspector, data collaboration options using CDM, or Data Exchange features and Python service integration.
Like what you see? You can continue exploring with our free academic license.
Modeling, not Programming: Model-Based Optimization in AMPL
Presented by: Dr. Robert Fourer, President, AMPL Optimization Inc.
Tuesday, November 10, 2-2:30pm
As optimization methods have been applied more broadly and effectively, a key factor in their success has been the adoption of a model-based approach. An investigator or analyst focuses on modeling the problem of interest, while the computation of a solution is left to general-purpose, off-the-shelf solvers.
Following a brief introduction to optimization in prescriptive (decision) analytics, this tutorial presents AMPL’s approach to optimization modeling and application development, contrasting its emphasis on model description to alternatives that rely more heavily on programming. The presentation is illustrated with a running example and with short case studies of AMPL applications in varied practical settings.
Presented by: Professor Roman Slowinski
Tuesday, November 10, 2:35-3:05pm
Join Professor Roman Slowinski (Co-ordinating Editor in Chief) of the European Journal of Operations Research (EJOR) who will talk about EJOR and give an overview of the title statistics, the type of papers the journal accepts and new initiatives in the journal. This will be a great opportunity to learn more about this high profile journal.
End-to-End FICO® Xpress Insight Tutorial: From Data to Decisions for Non-Technical Business Users
Presented by: Majid Bazrafshan
Monday, November 9, 1:05-1:35pm
You have a team with a great analytics background. They’ve developed advanced analytical tools using Python, R, or your current optimization solver. They’ve derived crucial insights from your data and figured out how your decisions shape your customers’ behaviors. Now it’s time to put these critical analytical insights into the hands of your non-technical business users.
In this tutorial, you’ll learn how FICO’s Xpress Optimization solutions (including Xpress Mosel, Xpress Workbench, Xpress Solver and Xpress Insight) make it possible to embed your analytic models in business user-friendly applications. See how to supercharge your analytic models with simulation, optimization, reporting, what-if analysis, and agile extensibility for your ever-changing business. Plus, you’ll discover how to use the new View Designer to reduce GUI development times from minutes to seconds.
From Model To App – Deploy Your Gams Models With Miro And Engine
Presented by: Steven P. Dirkse & Robin Schuchmann
Wednesday, November 11, 12:30-1pm
GAMS MIRO enables you to turn your GAMS models into full-fledged applications that are easy to deploy. An intuitive user interface allows you to interact with the underlying GAMS model, quickly create scenarios, compare results and much more. Choose from a variety of powerful charts, pivot tables, and other tools to gain deeper insight into the characteristics of your optimization problem. GAMS MIRO is seamlessly connected to GAMS Engine, a REST API designed to run in cloud environments. We will show how model calculations can be performed in a highly scalable cloud setup with one click.
Standard Pooling Problem – Build Your Optimization Skills with Python
Presented by: Cipriano Santos, PhD, Senior Technical Content Manager, Gurobi Optimization
Thursday, November 12, 12:30-1pm
During this tutorial, we will discuss the Standard Pooling Problem – a challenging problem common in the petrochemical refining, wastewater treatment, food processing, and mining industries. We will present two alternative formulations (formulated as Quadratically Constrained Quadratic Problems) using the Gurobi Python API and solve them with the Gurobi Optimizer to contrast their performance.
Modelling and solving with CP Optimizer
Presented by: Philippe Refalo
Friday, November 13, 1:05-1:35pm
CP Optimizer is IBM’s general constraint programming engine with an emphasis on solving scheduling models. Using a worked example, we present how to create, debug and improve the formulation of constraint programming models. We will also show recent performance improvements on large-scale resource-constrained project scheduling.
JMP®, a Division of SAS
JMP Statistical Software
Presented by: Kevin Potcner
Thursday, November 12, 2-2:30pm
See a demonstration of JMP Statistical Software by SAS. With its point-and-click interactive interface and dynamic visualizations, JMP is an ideal tool to quickly explore and analyze data. With a wide collection of graphical tools, statistical analysis techniques, and predictive modeling platforms, JMP is a great fit for beginner analysts all the way to advanced data scientists.
Lindo Systems, Inc.
Optimization Modeling Made Easy
Presented by: Mark Wiley
Tuesday, November 10, 1:05-1:35pm
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.
From Model to App with MATLAB
Presented by: Dr. Mary Fenelon, Product Marketing Manger
Monday, November 9, 12:30-1pm
MATLAB makes it easy to build optimization applications that can be deployed royalty-free as standalone executables or as web apps. In this tutorial you will learn how to use MATLAB for machine learning, optimization, and app building. In the first segment, you will see how to use MATLAB apps to prepare the data and to train a machine learning model. The trained load forecasting model provides input to the unit commitment model that is built with the problem-based workflow for optimization. In the final step, we show how to turn the optimization model into an app with App Designer.
The Optimization Firm
Interpretable Analytics and Machine Learning with ALAMO
Presented by: Dr. Yash Puranik
Monday, November 9, 2:35-3:05pm
This tutorial will summarize ALAMO’s key features and demonstrate its GUI, CLI, and Python interface. The ALAMO software provides interpretable data models through its novel optimization and adaptive sampling strategy and sophisticated features like constrained regression. ALAMO generates accurate models that are as simple as possible. Simultaneously, constrained regression ensures that these models satisfy relationships between the various variables in the data, dramatically enhancing the interpretability and maintainability of the models.
Advanced Analytics Model Review and Validation
Presented by: Dr. Irv Lustig, Optimization Principal, Princeton Consultants
Friday, November 13, 12:30-1pm
Acting as an independent third party, Princeton Consultants reviews analytics models and how they are deployed in a business. Through our Advanced Analytics Model Review and Validation service, we ask questions such as: What is a correct model? What data is being integrated and how? How are solutions published and used in the business? How sensitive are the answers to the inputs? Did the implemented model reflect the intentions of the practitioner?
In this tutorial, Irv Lustig will illustrate the importance of addressing these questions in the context of deploying advanced analytics models in practice, and discuss interesting findings from recent model reviews.
Exploratory Text Mining: An Inductive Approach to Text Analytics
Tuesday, November 10, 12:30-1pm
Business Analytics involves researching incident reports, corporate reports, social media, customer reviews and much more. It can be extremely time consuming, expensive and it is often impossible to read each and every relevant document. In this session, we will introduce participants to exploratory text mining, a powerful inductive approach in text analytics. We will present a variety of methodologies used in text mining to process text data and quickly identify relationships, trends, patterns that otherwise would remain buried in the mass of unstructured big data. We will also identify its limits and situations where a more deductive approach may be required. Exploratory text mining is a technique that every researcher should know to better discover new information and potentially obtain answers to specific research questions very quickly.
“Building and Solving Optimization Models with SAS”
Presented by: Ed Hughes, Principal Product Manager, Ed.Hughes@sas.com and Rob Pratt, Senior Manager, Advanced Analytics R&D, Rob.Pratt@sas.com
Wednesday, November 11, 4:30-5pm
SAS provides a broad and deep array of data and analytic capabilities, including data integration, statistics, data and text mining, econometrics and forecasting, and operations research. The SAS optimization, simulation, and scheduling features coordinate easily and fully with other SAS strengths in data handling, analytics, and reporting.
OPTMODEL from SAS provides a powerful and intuitive algebraic optimization modeling language and unified support for building and solving LP, MILP, QP, NLP, CLP, and network-oriented models. And because the OPTMODEL optimization modeling language is contained within the OPTMODEL procedure, a SAS software module, it integrates seamlessly with the entire family of SAS functions, procedures, and macros. We’ll demonstrate how you can use OPTMODEL to solve both basic and advanced problems, highlighting its newer capabilities and its support for both standard and customized solution strategies.
Simulation and Scheduling Software All in One!
Presented by: Ryan Welch Luttrell – Solutions Engineer (Simio LLC)
Thursday, November 12, 1:05-1:35pm
Simio is a premier simulation and scheduling software that allows you to expand traditional benefits of simulation to improve daily operations. In this tutorial, we will demonstrate Simio’s 3D rapid modeling capability to effectively solve real problems. Explore how a single tool can be used to not only optimize your system design, but also provide effective planning and scheduling. Come explore the Simio difference and see why so many professional and novice simulationists are changing to Simio.
Tips For Teaching Business Analytics in a Hybrid or Online Course
Presented by: Bryce Johnson
Wednesday, November 11, 2:35-3:05pm
In this tutorial, Bryce Johnson will share actionable tips on how to successfully teach a business analytics course in a hybrid or online course. The Stukent digital business analytics courseware and simulation cut down prep time and provides students with hands-on practice. The courseware has been approved by a board of industry experts so you know you’re teaching your students skills that will prepare them to enter the job market.
The AnyLogic Company
AnyLogic: The Platform for Simulation Modeling and State-of-the-Art AI Applications
Presented by: Arash Mahdavi, AI Program Lead, AnyLogic North America
Monday, November 9, 2-2:30pm
In this tutorial, we will discuss how you can leverage the unique features of AnyLogic to solve your business challenges with simulation. In addition to demonstrating the latest developments in conventional general-purpose simulation modeling, we will discuss the state-of-the art applications of simulations to train and test AI for business applications.