xpress#

A Party Scheduling Problem with FICO Xpress#

party1.ipynb Open In Colab Open In Deepnote Open In Kaggle Open In Gradient Open In SageMaker Studio Lab
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

Minimize the Pairwise Distance Ratio for N Points#

Paintshop Color Change Scheduling with FICO Xpress#

color_change_scheduling.ipynb Open In Colab Open In Deepnote Open In Kaggle Open In Gradient Open In SageMaker Studio Lab
Description: A scheduling problem demonstrating high-level modeling and manual solver tuning in FICO Xpress

Retrieve Solution pool with AMPL and Gurobi#

solution_pool.ipynb Open In Colab Open In Deepnote Open In Kaggle Open In Gradient Open In SageMaker Studio Lab
Description: This notebook describes how to retrieve multiple solutions from the solver’s solution pool. Optimization problems usually have several optimal solutions, one is returned by the solver but the others are discarded. These alternative solutions can also be retrieved by AMPL.

Unit Commitment MINLP with Knitro#

unit_commitment_minlp_mp2nl.ipynb Open In Colab Open In Deepnote Open In Kaggle Open In Gradient Open In SageMaker Studio Lab
Description: Solving a nonlinear Unit Commitment problem with Knitro using MP features for logic and multi-objective optimization. The goal of this notebook is to show a straightforward and clear way of using nonlinear solvers for complex models with logical expressions and also hierarchical multi-objective optimization.

Using multiple objectives in your model#

emulate_multiobjective.ipynb Open In Colab Open In Deepnote Open In Kaggle Open In Gradient Open In SageMaker Studio Lab
Description: We show how to use multiple objectives with Amplpy using a nonlinear Unit Commitment problem. We won’t be using native or emulated features from the solver interface, but emulating manually a lexicographic multiobjective problem.