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Technology Tutorials

Monday, November 5

Model-Based Optimization + Application Programming =
Streamlined Deployment in AMPL
Speakers: Robert Fourer, Filipe Brandão

AMPL offers the advantages of modeling in a specialized optimization environment combined with the power of application development via general-purpose programming. Optimization problems are formulated concisely and naturally in AMPL’s modeling language, promoting rapid development, reliable maintenance, and evaluation of multiple solvers and data sources. APIs for popular full-featured programming languages facilitate embedding of AMPL models and scripts into complex applications, with access to data management and interface development libraries. We illustrate using AMPL’s APIs for Python and R, and conclude with a preview of features for invoking Python within AMPL scripts.

Lumina Decision Systems
Tuesday, November 6

How to engage with your clients for more effective analytics
By: Max Henrion

In this workshop, Max Henrion will show how you can use Analytica as a key aid for more effective conversations with your clients, including how to:

  • Draw influence diagrams to help clients articulate their real objectives and decisions, and to work with them to frame and scope problems.
  • Use sensitivity analysis to help your clients understand what data and assumptions really matter and why.
  • Employ agile modeling methods to build decision tools that end users find usable and useful.
  • Design compelling visualizations to provide your clients a basis for informed and confident decisions.

    Practicing analysts and modelers will find these methods effective for improving client engagement in conjunction with almost any analytics software, but Analytica is unique in offering features designed specifically to support this approach to interactive modeling. Active participants will receive a free 12-month Analytica license. If you already have Analytica, you can give it to a colleague.

Sunday, November 4
8 – 8:45am

AnyLogic: The Most Comprehensive Simulation Modeling Platform for Business and Research

Rainer Dronzek, Regional Director, AnyLogic North America
Arash Mahdavi, Simulation Modeling Consultant, AnyLogic North America

In this tutorial, we will discuss how you can leverage unique features of AnyLogic simulation software and AnyLogic Cloud to solve your business challenges or perform scientific research. We demonstrate application of simulation in various domains and demonstrate state-of-the-art technologies that can take your simulation models to the next level in terms of sophistication and usefulness

Tuesday, November 6

Introducing the New API and Conic Solver in Artelys Knitro 11.0
Speaker: Richard Waltz, Senior Scientist

Artelys Knitro is the premier solver for nonlinear optimization problems. This software demonstration will highlight two key features in the new, major Knitro 11.0 release.  First, we will demonstrate the new callable library API.  This new API allows the user to build-up a model in pieces while providing special structures to Knitro.  Second, we will introduce the new solver in Knitro 11.0 specially designed for models with cone constraints.  Some benchmarking results will be provided.

DiDi Chuxing
Monday, November 5
5:15 – 6pm

Ride-sharing Services Research at Didi Chuxing

Didi Chuxing is the world’s leading mobile transportation platform. The company offers a full range of mobile tech-based mobility options for nearly 400 million users. As many as 20 million rides were completed on DiDi’s platform on a daily basis, making DiDi the world’s second largest online transaction platform. DiDi acquired Uber China in August 2016. DiDi is committed to working with communities and partners to solve the world’s transportation, environmental and employment challenges using big data-driven deep-learning algorithms that optimize resource allocation. In 2016, Didi was named one of the World’s 50 Smartest Companies by MIT Technology Review.


Sunday, November 4
4:30 – 5:15pm

How to get published and meet the editors session
Speaker: Simon Jones

How to get Published in Operations Research Journals addresses how to prepare and submit a manuscript using correct manuscript language, and how to structure an article.

Monday, November 5

End-to-End FICO® Xpress Insight Tutorial: From Data to Decisions for Non-Technical Business Users
Speaker: Jim Williams

You have a team with a great analytics background. They have developed advanced analytical tools using Python, R, or with your current traditional optimization solver. They have derived crucial insights from your data, and they’ve figured out how your decisions shape your customers’ behaviors. Now it’s time to put these critical analytical insights in the hands of your non-technical business users. In this tutorial, we will cover how FICO’s Optimization Suite (including Xpress Mosel, Xpress Workbench, and Xpress Insight) makes it possible to embed your analytic models in business user-friendly applications. Learn how you can supercharge your analytic models with simulation, optimization, reporting, what-if analysis, and agile extensibility for your ever-changing business.

Frontline Systems, Inc
Tuesday, November 6
10:30 – 11:15am

Tutorial: Preview of Analytic Solver V2019 for Windows, Macintosh, and Office 365
By: Daniel Fylstra, President, Frontline Systems Inc.

For many years, Frontline Systems has offered powerful data mining and machine learning, Monte Carlo simulation and risk analysis, and conventional and stochastic optimization in Analytic Solver® for Excel – on Windows. But use of Analytic Solver for Excel on Macintosh and the Web has involved challenges, due to differences within Excel.  That’s changing for the better in Analytic Solver V2019, which has been rewritten to work with new Excel internal APIs from Microsoft.  Attend this session to see a preview of Analytic Solver V2019: uniformly powerful and easier to use than ever – on Excel for Windows, Macintosh, and Office 365.

Sunday, November 4
2:15 – 3pm

GAMS – An Introduction
Presenters: Steven Dirkse & Lutz Westermann

We’ll introduce the key concepts of the GAMS language (e.g. sets, data, variables, equations) as we show how to build an optimization-based decision support application. Along the way, we’ll show how GAMS supports an easy growth path to larger and more sophisticated models and provides access to the most powerful large-scale solver packages. We will also look at some of the data management tools included in the GAMS system and show how to analyze and debug large problems using the various tools available within GAMS. Finally, we’ll show how our latest release supports integrating GAMS with object-oriented programming languages like C#, Python, and Java.


Gurobi Optimization
Monday, November 5
11:45am – 12:30pm

Advanced Heuristics with Gurobi
Speaker: Dr. Daniel Espinoza (Sr. Developer)

This talk covers one capability of MIP that is often overlooked: its ability to find and subsequently improve good quality solutions to exceedingly difficult problems. In particular, we will focus on techniques for using the Gurobi MIP solver as a heuristic, and a discussion on what makes a model more amenable to optimization.

Sunday, November 4
11:45am – 12:30pm

Solving Multi-Objective problems with CPLEX
Speaker: Ed Kotz, IBM

During this tutorial, you will learn how to use the Multi-Objective feature in the upcoming version of CPLEX Optimizer.  With the ability to specify combinations of lexicographic and blended objectives, it allows you to specify your goals very precisely.  By using this feature, you can save the trouble of developing your own multi-objective framework, and avoid the numerical difficulties often faced when combining vastly different objectives scales.
Sunday, November 4
11 – 11:45am

Data Driven Supply Chain Management Practices at
Speaker: Max Shen

As China’s largest retailer, online or offline, JD leverages advanced technologies such as AI to develop cutting-edge retail solutions that enable more personalize marketing and more efficient supply chain management, all aimed at improving the customer experience. In this tutorial, we will focus on a wide range of scenarios and applications in’s ecosystem, from both JD’s own e-commerce platform and its external business partners. We will cover the data-driven approaches used in these business scenarios to help improve supply chain efficiency and customer experience. We will also cover how technologies from fields such as operations research, data analytics, and machine learning are transforming the retail landscape.

JMP a Division of SAS
Monday, November 5

Analyzing Unstructured Text Data with the JMP Pro 14 Text Explorer
Speaker: Mia Stephens

In the era of big data, a majority of the data captured by organizations is unstructured.  Much of this unstructured data is in the form of text – from customer feedback, survey results, emails and texts, web reports, social media and other channels.  Analyzing this text-based information is particularly challenging, but the new Text Explorer platform in JMP 14 makes it easy.  This platform provides an efficient and interactive tool for analyzing unstructured text data, allowing us to easily extract information and transform unstructured text data into structured information.
In this session, we’ll use case studies to demonstrate how to use the JMP Text Explorer platform to analyze unstructured text data.  We’ll use a word cloud to visualize word frequency, use latent class analysis to cluster words, and apply other tools to understand underlying themes in unstructured text data.  We’ll also see how to create a document term matrix (DTM), and will use the resulting structured data in predictive modeling.

LINDO Systems, Inc
Monday, November 5
1:30 – 2:15pm

Optimization Modeling Tools from LINDO Systems
Presented by: Mark Wiley and Gautier Laude

Exceptional ease of use, wide range of capabilities, and flexibility have made LINDO software the tool of choice for thousands of Operations Research professionals across nearly every industry for over 30 years. 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 the tools you need to get up and running quickly. LINDO provides a set of intuitive interfaces to suit your modeling preference.

  • What’s Best! is an add-in to Excel that you can use to quickly build models that managers can use and understand.
  • LINDO has a full featured modeling language for expressing complex models clearly and concisely, and it has links to Excel and databases that make data handling easy.
  • LINDO API is a callable library that allows you to seamlessly embed the solvers into your own applications.

Pick the best tool for the job based upon who will build the application, who will use it, and where the data reside. Technical support at LINDO is responsive and thorough – whether you have questions about the software or need some modeling advise. Get started today. Visit our booth or to get more information and pick up full capacity evaluation licenses.

Tuesday, November 6
12:50 – 1:35pm

Experiential Machine Learning with MATLAB
Presenter: Elvira Osuna-Highley, PhD

There is a growing need to teach the next generation of scientists and engineers ever more complex concepts. It is critical that intuition is built quickly so that they can apply their knowledge to develop the technology of the future. This calls for experiential learning techniques that make concepts easy and fun to teach, learn and test. This tutorial will illustrate experiential learning using the Classification Learner app in MATLAB. You will see how to work through modules in MATLAB in order to build various classification models. This will give you the opportunity to understand the potential for using an experiential approach in the classroom as well as introducing you to tools that you may use in your research.

MemComputing, Inc.
Tuesday, November 6
7:30 – 8:15am

Overview of MemComputing Inc.
By: Fabio Traversa, PhD

Companies in all industries are seeking to optimize the efficiencies of their business environments in order to stay competitive. Data science is now coming to the forefront  across departments as they seek ways to leverage big data collections to implement solutions for improved efficiency and profitability. There are a set of problems associated with optimization, big data analytics and operations research among other areas, where companies are having to accept less than the optimal answer. The challenge lies within the fact that the size and complexity of the problems will grow exponentially as the inputs and constraints grow linearly. To find viable solutions, alternative methods are employed such as reducing the amount of data analyzed, breaking the problem up into smaller problems or accepting an incomplete answer when time reaches the threshold. This is not advantageous nor is it economical as efficiencies, innovations and revenues decline.

This tutorial presents a novel coprocessing architecture that is shifting the computing paradigm. Based on novel technology developed by MemComputing, Inc. its MemCPU Coprocessor platform speeds up computational time solving and finding accurate solutions for complex optimization and combinatorial problems of high economic value.


Modular Mining Systems
Sunday, November 6
1:30 – 2:15pm


Optimization  Direct
Monday, November 5

A DOCplex and ODH|CPLEX python primer
Presented by:  Robert Ashford & Joshua Woodruff

This short tutorial shows participants how to build a basic model using the DOCplex API in python. This session includes setting the python environment, reading data from a csv or spreadsheet, creating variables, objective functions, constraints, solving the model, and returning the results. Additionally this session points the participants to further reading so that they may expand their capabilities. Furthermore we will present the brand new ODH|CPLEX API for python, which improves solution times for large models.

Optimization Firm
Tuesday, November 6
12:05 – 12:50pm

Tuesday, November 6
8:15 – 9:00am

Quantitative Risk Analysis in Excel with @RISK
By Dr. Raul Castro

This tutorial will guide you in the use of @RISK for analyzing historical data and making better decisions in an uncertain business environment.
@RISK is part of Palisade’s Decision Tools Suite and runs as an add-in for MS Excel. It provides all the features you need to quantify and understand risks with the support of Monte Carlo Simulation, including graphical capabilities and quick reports to help you present results to a non-technical audience.

Provalis Research
Tuesday, November 6
2:45 – 3:30pm

The Different Text Analytics Approaches used for Business Analytics
Speaker: Normand Peladeau

Text analytics can provide you with real value by helping you quickly extract meaningful information from your text data such as incident reports, corporate reports, social media, customer reviews and much more. However, Text Analytics doesn’t work the same way for everyone. To make text analytics work for you, you need to know some of the pitfalls to avoid the pratfalls. We will show you techniques and methods you can deploy, what’s behind them and what to watch out for.

Responsive Learning Technologies
Tuesday, November 6
4:35 – 5:20pm

Online games to teach operations and supply chain management
Presented by: Sam Wood, President

Littlefield Technologies, the Supply Chain Game, and the Sourcing Game are online competitive assignments used to teach topics including process analysis, inventory control, supply chain management, and sourcing and purchasing.   We will describe the games’ learning objectives, typical assignments, and actual game results.

Monday, November 5
11 – 11:45am

Building and Solving Optimization Models with SAS
Presented by: 
Ed Hughes, Principal Product Manager,
Rob Pratt, Senior Manager, Advanced Analytics R&D, 

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.

Simio Simulation & Scheduling Software
Tuesday, November 6
2 – 2:45pm

Simulation and Scheduling Software All in One!
Presented by: Renee Thiesing and Katie Prochaska (Simio LLC)

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.

Sunday, November 4
8:45 – 9:30am

Marketplace Optimization and Data Science at Uber
Presenters: Hamid Nazerzadeh, Uber & University of Southern California
Alice Lu, Senior Data Scientist, Uber Technologies, San Francisco, CA

Marketplace is the center of Uber’s business, where riders and drivers come together at extraordinary scale. The data science team tackles problems such as optimizing Uber’s short and long term pricing mechanisms; efficiently matching incoming trip requests in Uber’s dispatch system; developing innovative incentive schemes that reward riders and drivers for choosing our network; and providing optimal routes and positioning suggestions to save time for everybody. In this presentation, we discuss in more details some of these challenging and innovative projects.

Sunday, November 4
5:15 – 6pm

Geo-Testing for Real-World Marketing
Speaker: Tom Wentworth

Optimized geographic testing is becoming a popular method for measuring the value of marketing interventions that are not amenable to more standard controlled testing methods, but getting the method to work in a real-world business environment is not always straightforward. In this tutorial, we will give an overview of geo-testing methods at Wayfair. Using e-commerce marketing as a case study, we will cover practical approaches including:

  • When and why to choose geo-testing as opposed to other more standard techniques
  • Test design and optimization to generate national results from local tests
  • Quantifying and avoiding “geo-leakage”
  • Test design methods for cost reduction while retaining statistical power