AMPL Forum

AMPL at INFORMS Annual Meeting 2022

Join us October 15-19, 2022 at the INFORMS Annual Meeting in Indianapolis.
AMPL will be a Diamond Sponsor and will have a booth in the exhibit area.

Our conference presentations will feature an introduction to model-based optimization,
surveys of exceptional new features, and case studies of AMPL in action:

  • Technology Workshop, Saturday, October 15, 1:00-3:30 pm (Indianapolis Convention Center, 106)
  • Technology Tutorial, Sunday, October 16, 5:00-5:35 pm (Indiana Convention Center, Wabash 1)

Learn why the fastest optimization toolchains run AMPL.

Technology Workshop, Saturday, October 15, 1:00-3:30 pm

Indianapolis Convention Center, Room 106

Adding Optimization to Your Applications, from Prototyping to Deployment: How AMPL is Making It Faster and Easier

Speaker: Robert Fourer, AMPL Optimization Inc.

Optimization is the most widely adopted technology of Operations Research and 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?
  • How can you deploy optimization in modern cloud and container environments?

In this presentation, we show how AMPL gets you going without elaborate training, extra programmers, or premature commitments. We specially highlight new AMPL features that make optimization modeling faster, easier, and more effective than ever.

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 and speed of execution while maintaining ease of use.

The presentation continues by taking a single example through successive stages of the optimization modeling lifecycle, highlighting recent enhancements:

  • Prototyping in an interactive command environment, with a new solver interface that accepts more natural modeling language expressions
  • Development of optimization procedures via AMPL’s built-in scripting language and enhanced spreadsheet/database interfaces
  • Integration through APIs to widely used programming languages, including Python with new notebook support
  • Deployment using new, flexible installation and licensing support

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. Several case studies of AMPL applications round out the presentation by showing how model-based optimization has been successful in varied areas of analytics practice.

Technology Tutorial, Sunday, October 16, 5:00-5:35 pm

Indiana Convention Center, Wabash 1

Advances in Model-Based Optimization with AMPL

Speaker: Robert Fourer, AMPL Optimization Inc.

Optimization has been fundamental to OR and Analytics for as long as there have been computers, yet we are still finding ways to make optimization software more natural to use, faster to run, and easier to integrate with application systems. This presentation offers a quick tour of ways that AMPL’s modeling framework has been enhanced to support optimization in today’s challenging applications. Topics include:

  • Expressing objectives and constraints more directly and understandably
  • Exchanging data and results more directly and efficiently, with spreadsheets and with database systems
  • Building better interfaces to applications using snapshots, callbacks, and other new features of AMPL’s APIs for popular programming languages
  • Deploying optimization in cloud environments and containers

To complement these feature advances, the presentation concludes by describing ways that AMPL is making model-based optimization more accessible, through the new Community Edition, a rewritten NEOS Server client, and free Model Colaboratory examples for teaching and learning optimization.