highlights#
A Party Scheduling Problem with FICO Xpress#
Description: A scheduling problem for visitor-host assignments. Feasibility version (no objective function). Demonstrates high-level modeling in AMPL MP, AMPL Python API, and tuning in FICO Xpress
Author: Gleb Belov (13 notebooks) <gleb@ampl.com>
AMPL Bin Packing Problem with GCG#
Description: Dantzig-Wolfe decomposition for Bin Packing Problem with GCG
Author: Jürgen Lentz (8 notebooks) <lentz@ampl.com>
AMPL Capacitated p-Median Problem with GCG#
Description: Dantzig-Wolfe decomposition for Capacitated p-Median Problem with GCG
Author: Jürgen Lentz (8 notebooks) <lentz@ampl.com>
AMPL Christmas Model created by ChatGPT#
Description: Christmas model generated by ChatGPT
AMPL Model Colaboratory Template#
Description: Basic notebook template for the AMPL Colab repository
Handling AMPL Errors and Warnings: ErrorHandler in amplpy#
Notebooks > Handling AMPL Errors and Warnings: `ErrorHandler in amplpy <../notebooks/handling-ampl-errors-and-warnings-errorhandler-in-amplpy.html>`_
Description: Shows how to use amplpy.ErrorHandler and amplpy.AMPLException to intercept, filter, and route AMPL errors and warnings — covering default raise behaviour, custom recovery strategies, and logging integration.
Author: Jürgen Lentz (8 notebooks) <lentz@ampl.com>
Inspecting AMPL Models: expand and show with amplpy#
Notebooks > Inspecting AMPL Models: `expand and show with amplpy <../notebooks/inspecting-ampl-models-expand-and-show-with-amplpy.html>`_
Description: Demonstrates the ampl.show(), ampl.expand(), and entity-level expand() methods introduced in amplpy 0.17.0, using the classic diet problem as a running example.
Author: Jürgen Lentz (8 notebooks) <lentz@ampl.com>
Intercepting AMPL Output: OutputHandler and Kind in amplpy#
Notebooks > Intercepting AMPL Output: `OutputHandler and Kind in amplpy <../notebooks/intercepting-ampl-output-outputhandler-and-kind-in-amplpy.html>`_
Description: Shows how to use amplpy.OutputHandler and amplpy.Kind to intercept, filter, and route AMPL interpreter output — covering silent solving, solver log capture, and structured logging by output kind.
Author: Jürgen Lentz (8 notebooks) <lentz@ampl.com>
Logistic Regression with amplpy#
Description: Logistic regression with amplpy using exponential cones
Minimize the Pairwise Distance Ratio for N Points#
Description: Minimize the pairwise distance ratio of N points with FICO Xpress
Tags: amplpy, highlights, nonlinear, quadratic, global-optimization, local-optimization, trigonometric, xpress
Author: Gleb Belov (13 notebooks) <gleb@ampl.com>
Multi-Objective Knapsack Problem with AMPLPY#
Description: knapsack problem using multiple objectives, setting objective-specific options
Tags: multi-objective, multi-objective-options, lexicographic-objectives, knapsack, amplpy, highlights
Author: Jürgen Lentz (8 notebooks) <lentz@ampl.com>
N-Queens#
Description: How can N queens be placed on an NxN chessboard so that no two of them attack each other?
Author: Gleb Belov (13 notebooks) <gleb@ampl.com>
Optimize your Christmas Tree to Global Optimality#
Description: Optimize the placement of ornaments on a christmas tree.
Quick Start using Pandas dataframes#
Description: Quick Start using Pandas dataframes to load and retrieve data
Quick Start using lists and dictionaries#
Description: Quick Start using lists and dictionaries to load and retrieve data
Robust Linear Programming with Ellipsoidal Uncertainty#
Description: AMPL Modeling Tips #6: Robust Linear Programming
Author: Gleb Belov (13 notebooks) <gleb@ampl.com>
Setting and Getting AMPL Options in amplpy#
Description: Shows every way amplpy exposes to set and get AMPL options — snake_case methods, dict-style indexing, camelCase aliases, and per-solve keyword overrides — covering interpreter options, solver-specific option strings, value types, and restore patterns.
Author: Jürgen Lentz (8 notebooks) <lentz@ampl.com>
Simple sudoku solver using logical constraints (with GUI)#
Description: Simple sudoku model with two formulations: as a Constraint Programming problem using the alldiff operator and as a MIP. Note that the CP formulation is more natural but it needs a solver supporting logical constraints or a MIP solver with automatic reformulation support (see [here](https://mp.ampl.com/) for more information).
Author: Christian Valente (5 notebooks) <ccv@ampl.com>