Join us October 20-23, 2024 in Seattle, Washington
AMPL will be a Bronze Sponsor for the 2024 event. Visit us at booth 219 for a live demo.
Location: SUMMIT-345
Presented by: Filipe Brandão and Robert Fourer
Python and its vast ecosystem are great for data pre-processing, solution analysis, and visualization, but Python’s design as a general-purpose programming language makes it less than ideal for expressing typical complex optimization problems. AMPL is a declarative language that is designed for describing problems and that integrates naturally with Python.
In this presentation, we’ll survey a range of contexts where AMPL and Python work together to make optimization software simpler to use, faster to run, and easier to integrate with enterprise systems:
You’ll also see how generative AI technology is enabling a rapid development process for both AMPL and Python, reducing the time and effort to produce working applications that are ready for end-users.
Location: CC-North 231B
Advances in Model-Based Optimization with AMPL
Presented by: Filipe Brandão
The ideal of model-based optimization is to describe your problem the way you think about it, and then let the computer do the work of getting a solution. Recent enhancements aim to bring the AMPL modeling language and system closer to this ideal. Using a variety of modeling language extensions, common formulations are described more naturally, with the AMPL translator, the AMPL-solver interface, or the solver itself doing most of the needed transformations. Extensions described in this presentation include quadratic expressions, logical operators and constraints, simple near-linear and nonlinear functions, and combinations of these together with linear terms. All are supported by a new C++ AMPL-solver interface library that can be adapted to handle the multiple detection and transformation strategies required by large-scale solvers.
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