Technology Tutorials


Developing Optimization Applications Quickly And Effectively With Algebraic Modeling

Robert Fourer, AMPL Optimization Inc.

Can you negotiate the complexities of the optimization modeling lifecycle, to deliver a working application before the problem owner loses interest? Algebraic languages streamline the key steps of model formulation, testing, and revision, while offering powerful facilities for embedding models into larger systems and deploying them to users. This presentation introduces algebraic modeling for optimization by carrying a single illustrative example through multiple contexts, from interactively evolved formulations to scripted iterative schemes to enterprise applications.


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Anylogic, The Simulation Modeling Software for Professionals

Derek Magilton, AnyLogic

AnyLogic offers unique capabilities in the simulation world and we will guide you through a series of models that utilize Agent Based, Discrete Event and Systems dynamics methodologies. We recently introduced full GIS integration so you will see how we can incorporate geographical and spatial elements into your models in real time. has evolved from a pure modeling and optimization library, allowing you to rapidly develop and deploy on-premises and cloud optimization solutions.


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ArtelysCrystal: A Software for Power Supply-demand Adequacy Analysis

Guillaume Jean Tarel, Artelys

This presentation focuses on the use of Artelys Crystal Super Grid, a power systems modeling software developed by Artelys. Our users are investors, regulation authorities and independent system operators (ISO), ministries, consultants or transmission system operators (TSO/RTO). Their objective is to evaluate in detail the interest of specific projects (generation/transmission/storage) in terms of revenue, social welfare, pollutant emissions, and security of supply in a region. To this purpose, Artelys Crystal Super Grid uses built-in libraries of power assets and indicators, along with a powerful optimization engine, to simulate systems with tens of interconnected regions on an hourly basis. Its intuitive interface allows for efficient analysis, comparison and evaluation of large number of scenarios.


Recent Advances in the Artelys Knitro Nonlinear Optimization Solver

Artelys Knitro is the premier solver for nonlinear optimization problems. This software demonstration will highlight the latest Knitro developments, including a new mixed-integer nonlinear programming (MINLP) algorithm able to handle non-relaxable integer variables, and new object oriented and R interfaces. The demo will also provide an overview of how to effectively use Knitro in a variety of environments and applications.


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Booz Allen – Argo™ – Free, Powerful Monte Carlo Simulation


Organizations face complex decisions that require advanced decision support to solve their most challenging problems. To meet these challenges, Booz Allen Hamilton leveraged simulation R&D combined with wide-ranging experience applying simulation analytics to inform client strategies in the development of Argo™, a spreadsheet Monte Carlo simulation tool tailor made for decision trade-off analysis when facing Risk and Uncertainty.

 The Argo™ software’s processing speed enables models to serve as investigative tools that allow decision makers to explore trade-off scenarios, gain greater insight into the impacts of Risk and Uncertainty, and measure the effectiveness of potential decision strategies – without ever leaving the meeting room.

At Booz Allen, consultants have used Argo™ as the primary spreadsheet simulation tool for the past three years – delivering dynamic spreadsheet simulation models that improve client understanding of Risk and Uncertainty.  Now we are offering Argo™ completely free for use by analysts and decision makers to solve their most challenging problems.


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Anaconda: One Platform For Analytics, Modeling, And Applications

Michael Grant, Continuum Analytics

The answer to the question, “What is Python?” has evolved over the decades. In the 1990s, the Python language excited programmers with its features and quirks, and helped spark a revolution in open-source software development. In the 2000s, innovations such as NumPy, Matplotlib, and IPython led to the wide adoption of Python as a modeling environment for engineers and scientists alongside established tools such as MATLAB. Today, Python has matured into an enterprise-ready data science platform, empowering the development of data-rich applications at home on the desktops of business analysts, data scientists, and application developers alike.

In this talk we introduce you to Anaconda, the modern open source analytics platform powered by Python. We will demonstrate Jupyter Notebook for developing live documents integrating data, computation, visualizations, and text. You’ll see how your favorite optimization packages integrate seamlessly into this environment, replacing the traditional modeling framework. And once the models are set, we’ll show you how easy it is to deploy them to the desktop with rich visualizations and interactivity using Bokeh server.

Modern enterprises are demanding faster development cycles with greater flexibility that can meet the fast paced, ever changing needs of the world around us. Anaconda fuses together the phases — from data ingest to exploration through to deployment — eradicating the traditional data analytics bottlenecks and hurdles.


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How to Deploy your SAS, R, Python Models to Empower Non-technical Business Users

Horia Tipi and Libin Varghese, FICO

Your analytic data scientists are hard at work finding patterns in your data. They’ve figured out how your decisions and actions shape your customers’ reactions and behaviors. They’ve used advanced analytic platforms like SAS, or collaborative open source platforms like Python and R. Their p-values are low, their R-squares are high, and the only thing standing between you and your much-awaited incremental profits is the question: “How do I put these values in the hands of my business analysts and users?” In this tutorial, we will cover how FICO’s Optimization Suite (including Xpress and Optimization Modeler) make it possible to incorporate your analytic models in user-friendly business-user facing applications. Learn how you can supercharge your analytic models with simulation, optimization, reporting, what-if analysis, approval workflows and agile extensibility.


Efficient Parallel Linear and Mixed Integer Programming in FICO Xpress

Oliver Bastert, FICO

FICO Xpress provides parallel algorithms for linear, mixed integer and non-linear programming. In this session, we’ll detail the dual parallel simplex that complements the parallel barrier implementation. For mixed integer programming, Xpress 8.0 provides a new parallel MIP implementation that is based on a new task manager that optimizes deterministically independent of platform and number of CPU cores. Non-linear provides parallel multi-start capabilities and has adopted the new parallel tree.


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Creating Interactive Analytics on the Web with Forio Epicenter

Michael Bean, Forio

Forio Epicenter makes your model available to hundreds of people within your organization through the browser. Forio Epicenter supports R, Python, Julia and other languages for optimization, machine learning, simulation, and other analytics techniques. The platform is enterprise-compatible with the ability to integrate with an organization’s existing IT infrastructure and tiered control for thousands of users. We will start with an introduction to Epicenter and sample interactive online models. Then we’ll divide the workshop into two parts. In the first part we will teach you how to get your analysis on a server so it can be shared. In the second part we’ll focus on creating a user interface for your model.


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Data Mining, Simulation and Optimization in Your Web Browser

Daniel H. Fylstra, Frontline Systems, Inc.

With Frontline Solvers, everything you need – including your data – for forecasting, data mining and text mining, Monte Carlo simulation and risk analysis, and conventional and stochastic optimization is available at your fingertips in your web browser. We’ll show how you can pull data from SQL Server databases and Apache Spark Big Data clusters, solve large-scale models, and visualize results in Tableau and Power BI – without leaving your browser. Given time, we’ll also show how you can do all of these things in your spreadsheet.


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The Role of Algebraic Modeling Languages in Industrial Optimization

Steven P. Dirkse, GAMS Development Corporation

Algebraic Modeling Languages (AML) are one of the success stories in Operations Research. GAMS is one of the prominent AMLs and during this workshop we will showcase fundamental principles, recent and ongoing developments, and our view of the future of AMLs. We will review some application examples done by our clients in academia and industry, in which optimization is an important element. These projects give insight into the complexity of tasks as well as the variety of environments in developing and deploying optimization applications.


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The Business Case for Optimization and Gurobi

This presentation will consider the process that customers go through when determining whether optimization is the right tool for addressing a particular business problem. We’ll look at a few examples of business situations that our customers and consulting partners have faced, and we’ll talk about how they used the available optimization tools and technologies to address them.


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Discover How to Use the IBM Decision Optimization Python API

Vincent Beraudier, Lead Architect – IBM Decision Optimization with Python

In this tutorial, you will learn how to use the IBM Decision Optimization Python API in a Notebook environment to create optimization models, invoke the CPLEX engines either locally or on cloud, and create application prototypes.


Discover How to Use the IBM SPSS Modeler Gold

Ted Fischer, IBM SPSS Modeler Gold

In this tutorial, you will learn how to use IBM SPSS Modeler Gold for forecasting and clustering.


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Optimization Modeling Tools from LINDO Systems

Mark A. Wiley, LINDO Systems Inc

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

• What’sBest is an add-in to Excel that you can use to quickly build spreadsheet models that managers can use and understand.
• LINGO 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.

You can 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 guidance on handling a particular application.Get started today. Visit our booth or to get more information and pick up full capacity evaluation licenses to try them out on your toughest models.


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Multi-echelon Inventory Optimization to Drive Analytical Decision Making

Jeff Pittman, Logility

Beyond setting inventory targets, the multi-echelon inventory model can be used to analyze a variety of critical business decisions. In this session we will show how MEIO is used analytically to provide data based decision support for:

• Extending a Finished Goods Model Up-Stream to Include Manufacturing, Procurement and Partners

• Modeling Inventory Policy on New Products and Innovation

• Modeling impact of procurement decisions

• Modeling Impact of lead times, frequencies and cycles

• Modeling impact of customer segmentation

• Modeling impact of Lean implementation


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Solving Large Scale Optimization Problems using CPLEX Optimization Studio

Robert Ashford and Alkis Vazacopoulos, Optimization Direct/IBM

Recent advancements in Linear and Mixed Programing give us the capability to solve larger Optimization Problems. CPLEX Optimization Studio solves large-scale optimization problems and enables better business decisions and resulting financial benefits in areas such as supply chain management, operations, healthcare, retail, transportation, logistics and asset management. In this tutorial using CPLEX Optimization Studio we will discuss modeling practices, case studies and demonstrate good practices for solving Hard Optimization Problems. We will also discuss recent CPLEX performance improvements and recently added features.


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Text Analytics Software

Normand Peladeau, Provalis Research

QDA Miner is easy to use qualitative and mixed methods software that meets the needs of researchers performing qualitative data analysis and would like to code more quickly and more consistently larger amounts of documents. It offers high level computer assistance for qualitative coding with innovative text search tools that help users speed up the coding process as well as advanced statistical and visualization tools. Users with even bigger text data can also take advantage of WordStat. This add-on module to QDA Miner can be used to analyze huge amounts of unstructured information, quickly extract themes, find trends over time, and automatically identify patterns and references to specific concepts using categorization dictionaries.


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Optimization and Discrete-Event Simulation with SAS

Rob Pratt and Ed Hughes, SAS Institute, Inc.

We’ll demonstrate two of the major capabilities of SAS/OR, the primary operations research product from SAS. We’ll see how SAS/OR’s OPTMODEL procedure enabled us to model and solve a difficult political redistricting problem. We’ll also discuss how we used SAS Simulation Studio (a SAS/OR component) to model the operations of a neonatal intensive care unit to improve outcomes for its patients and study how the unit can improve its staffing policies.


SAS Edu/Gap

Analyzing Unstructured Data from Presidential Debates using SAS TextMining

André de Waal, Global Academic Program

SAS Text Miner can be used to uncover underlying themes or concepts contained in large document collections, automatically group documents into topical clusters, classify documents into predefined categories, and integrate text data with structured data to enrich predictive modeling endeavors. A transcript form a recent presidential debate will be analyzed with SAS Text Miner. The results from the analysis will be explained and compared to general comments made in the general media.


The Analytics Tool Kit:A Case Study with JMP Pro

Mia L. Stephens, SAS Institute Inc

The modern business world is defined, in part, by the volumes of data produced daily. The challenge, for any successful manager within a productive and highly-functioning organization, is to be able to put this data to use in guiding decision-making and strategy. We present important concepts and techniques for developing predictive models with complex and messy data sets using JMP Pro, a desktop statistical package from SAS. We use a case study to illustrate tools for data preparation, demonstrate interactive visualization techniques, and discuss the importance of validation and validation statistics to gauge model accuracy. Then, we present core modeling techniques, including logistic regression, classification trees, neural networks, and three penalized regression techniques: Lasso, Elastic Net, and Ridge. Finally, we see how to interactively reduce models, and discuss methods for model visualization, comparison and selection.


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Build an Analytics Platform, Not a Big Data Platform

Todd Jones, WebbMason

2015 was the year of the Big Data proof of concept. Many IT groups showed how easy it was to load structured and unstructured data to create a data lake in Hadoop. Following this POC, we have witnessed many companies become stagnant in their ability to convey the value of Big Data beyond data storage. The value of Big Data is not the ability to store data, but the insights and analytics that can be developed from this data. 2016 will be the year of the Analytics Platform. Whether your data is big, small or somewhere in between, the Analytics Platform is a hub where all analytics work across the business can be centralized, automated, and reused. While the foundation of the Analytics Platform is Hadoop, it is supported by analytic technologies, an Analytics SWAT team, and repeatable processes for engaging with business units to deliver value. Join us in exploring how you can transform Big Data into an Analytics Platform and position your company to gain the competitive insights Big Data offers. Attendees will learn:

• How to transform the discussion from Big Data technologies to Analytics Platforms

• The core components of an Analytics Platform and how they relate – data storage, data pipeline management, data science, and data visualization

• The skills required when creating an Analytics SWAT teamA 2016 roadmap to leverage the power of Big Data to develop competitive insights