Examples

Many Jupyter notebooks with examples are available on the AMPL Model Colaboratory and the new book Hands-On Mathematical Optimization with AMPL in Python 🐍.

You should also check out our collection of interactive Streamlit Apps and learn how easy you can build your own apps.

AMPL Model Colaboratory is a collection of AMPL models in Jupyter Notebooks that run on platforms such as Google Colab, Kaggle, Gradient, and AWS SageMaker.

Available at: ampl.com/colab.

You can use the Christmas notebook written by ChatGPT to get started:

BTW: you can even ask ChatGPT to write models for you! If it makes mistakes you can ask for help in our new Discourse Forum!

The repository of notebooks MO-BOOK: Hands-On Mathematical Optimization with AMPL in Python 🐍 introduces the concepts and tools of mathematical optimization with examples from a range of disciplines.

Available at: ampl.com/mo-book.

Build and share data apps quickly with Streamlit - no front-end experience necessary.

Available at: ampl.com/streamlit.

Example files

This section lists a few examples in Python. These are the same files that can be found in the amplpy Github repository, and show the basic usage of the Python API.

Example 1: First steps

first_example.py

This example shows how to

• read an AMPL model

• reassign values to parameters

• solve the model

• display the objective function value

Example 2: Get and set AMPL options

options_example.py

This example shows how to:

• get and set AMPL options

Example 3: Assign all data to a model and solve it

diet_model.py

This example shows how to:

• Assign all the data necessary to generate a model instance programmatically

Example 4: Build an efficient frontier

efficient_frontier.py

This example shows how to:

• build an efficient frontier by repeteatly solve a portfolio problem in AMPL

Example 5: Simple heuristic

tracking_model.py

This example shows how to:

• Do a simple heuristics for solving a QMIP problem, using the relaxed solution as a hint