ampl

AMPL - solve multiple models in parallel

multiproc.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Solve multiple AMPL models in parallel in Python with amplpy and the multiprocessing modules.

AMPL - spreadsheet handling with amplxl

amplxl.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Basic example of reading/writing data into/from a .xlsx spreadsheet with amplxl

Introduction to Linear and Integer Programming

intro_to_linear_prorgramming.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Basic introduction to linear programming and AMPL via a lemonade stand example

Introduction to Mathematical Optimization

intro_to_optimization.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Basic introduction to optimization and AMPL via unconstrained optimization

Network Linear Programs

network.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Basic introduction to network linear programms and AMPL via max flow and shortest path problems

Production Model

production_model.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Basic introduction to AMPL’s indexed entities and the Pygwalker Python package via a lemonade stand example

Solving simple stochastic optimization problems with AMPL

newsvendor.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Examples of the Sample Average Approximation method and risk measures in AMPL

Stochastic Capacitated Facility Location Problem

stochastic_facility_location.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: This notebook illustrates modeling a stochastic facility location problem using a mixed-integer programming approach. Facility location decisions are pivotal, typically requiring substantial investments that have far-reaching social, economic, and environmental consequences.