AMPL at OR 23
Join us August 29 – September 1, 2023 in Hamburg, Germany.
This conference is a place to exchange ideas and interact with other academics, researchers, and practitioners in the fields of Operations Research, Management Science, Data Science, and Analytics. The OR 2023 will take place from August 29 to September 1, 2023 at the University of Hamburg.
What’s New in Modeling Systems
Location: R 0079, VMP5
Stream: Software for OR
Chair: Filipe Brandão
Presented by: Filipe Brandão
Advances in Model-Based Optimization with AMPL
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.
Location: ESA B
Stream: PC Stream
Chair: Filipe Brandão
Presented by: Filipe Brandão
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 complex real-world optimization problems. AMPL is a declarative language that is designed for describing optimization problems and that integrates naturally with Python. In this presentation, you’ll learn how the combination of AMPL modeling with Python environments and tools have made optimization software more natural to use, faster to run, and easier to integrate with enterprise systems.