Gyorgy Matyasfalvi (15 notebooks)

AMPL Development Tutorial 1/6 – Capacitated Facility Location Problem

AMPL Development Tutorial 2/6 – Stochastic Capacitated Facility Location Problem

AMPL Development Tutorial 3/6 – Benders Decomposition via AMPL scripting

3_benders_stoch_floc.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: In this third installment of our six-part series, we continue our exploration by addressing the complexities introduced by the stochastic programming formulation presented in part two.

AMPL Development Tutorial 4/6 – Benders Decomposition via PYTHON scripting

4_benders_in_python_stoch_floc.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: In this fourth installment of our six-part series, we advance our exploration by demonstrating how to adapt our AMPL script for use with AMPL’s Python API.

AMPL Development Tutorial 5/6 – Parallelizing Subproblem Solves in Benders Decomposition

5_benders_parallel_stoch_floc.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: In the fifth installment of our six-part series, we delve deeper by showing how to evolve our Benders decomposition Python script from a serial execution to one that solves subproblems in parallel.

AMPL Development Tutorial 6/6 – Implementing Benders Decomposition with ampls

6_benders_ampls_stoch_floc.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: This concluding notebook in our six-part series delves into enhancing the efficiency of our decomposition algorithm by utilizing AMPL Solver Libraries (ampls).

Capacity expansion of power generation

capacity_expansion.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Models the extensive form of a deterministic multi-stage capacity expansion problem. In this model we can have multiple resources of the same type which have identical properties. The model can be further developed into a stochastic one.

Debugging Model Infeasibility

debug_infeas.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: This notebook offers a concise guide on troubleshooting model infeasibility using AMPL’s presolve feature and other language capabilities.

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

Plot feasible region

plot_feasible_region.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Plot the feasible region and optimal solution for a simple two variable model using AMPL’s Python API.
Tags: lecture, lp, simple

Pricing and target-market

pricing_and_target_market.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Formulate a pricing optimization and target-market problem as a MILP.

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

Unit Commitment for Electrical Power Generation

unit_commitment.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: This notebook illustrates the power generation problem using AMPL. The original version featured the Gurobi solver. By default, this notebook uses the HiGHS and CBC solvers.