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AMPL at Analytics 2019

Join us April 14-16, 2019 at the INFORMS Business Analytics Conference.
AMPL is a Gold Sponsor and is exhibiting at booth #9.

Learn more about model-based optimization at our AMPL-related events:

All conference presentations take place at the JW Marriott Hotel, 110 East 2nd Street, Austin, Texas.
 


Technology Workshop, Sunday, April 14, 3:00-4:45pm

JW Marriott Hotel, Room 303

Adding Optimization to Your Applications, Quickly and Reliably:
From Prototyping to Integration with AMPL

Speaker: Robert Fourer, AMPL Optimization Inc.

Optimization is the most widely adopted technology of Prescriptive Analytics, but also the most challenging to implement:

  • How can you prototype an optimization application fast enough to get results before the problem owner loses interest?
  • How can you develop optimization-based procedures to get results you can use, within your time and resource requirements?
  • How can you integrate optimization into your enterprise’s decision-making systems?

In this presentation, we show how AMPL gets you going without elaborate training, extra programmers, or premature commitments. We start by introducing model-based optimization, the key approach to streamlining the optimization modeling cycle and building successful applications today. Then we demonstrate how AMPL’s design of a language and system for model-based optimization is able to offer exceptional power of expression while maintaining ease of use.

The remainder of the presentation takes a single example through successive stages of the optimization modeling lifecycle:

  • Prototyping in an interactive command environment.
  • Development of optimization procedures via AMPL’s built-in scripting language.
  • Integration through APIs to widely used programming languages, including C++, C#, Java, and MATLAB, and featuring the popular data science languages Python and R.

Our example is simple enough for participants to follow its development through the course of this short workshop, yet rich enough to serve as a foundation for appreciating model-based optimization in practice.
 


Technology Tutorial, Monday April 15, 3:40-4:30pm

JW Marriott Hotel, Room 304

Model-Based Optimization + Application Programming = Streamlined Deployment in AMPL

Speaker: Robert Fourer, AMPL Optimization Inc.

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 Python API and new AMPL features that leverage Python for optimization application development.
 


Optimization Track, Tuesday April 16, 10:30-11:20am

JW Marriott Hotel, Room 304

Combining Choice Modeling and Nonlinear Programming to Support Business Strategy Decisions

Speaker: John V. Colias, Decision Analyst Inc. and University of Dallas

Using a case study with simulated data, we demonstrate how to integrate a choice model into a customer lifetime value (CLV) simulation and optimization tool. While the methodology is validated with AT&T data, due to the proprietary nature of the results, only results using simulated data will be presented.

Because the typical choice modeling study includes both nominal and numeric attributes as drivers of customer value, purchase probabilities, market share, and revenue, the nonlinear programming problem becomes non-trivial, requiring the use of state-of-the-art algorithms. Our solution will make use of several nonlinear programming algorithms using AMPL software.

From this presentation, industry experts will understand the features and benefits of choice modeling, required resources to implement and combine choice modeling and nonlinear programming, and the types of business strategy objectives that can be supported by combining Choice Modeling and Nonlinear Programming.