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AMPL - solve multiple models in parallel

Notebooks > 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.
Tags: ampl, python, amplpy, multiprocess, parallel-computing, stochastic-programming
Author: Nicolau Santos (3 notebooks) <nfbvs@ampl.com>

AMPL - spreadsheet handling with amplxl

Notebooks > 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
Tags: ampl, amplxl, spreadsheet, excel, xlsx
Author: Nicolau Santos (3 notebooks) <nfbvs@ampl.com>

AMPL Development Tutorial 1/6 – Capacitated Facility Location Problem

Notebooks > AMPL Development Tutorial 1/6 – Capacitated Facility Location Problem
1_floc.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: This notebook marks the beginning of a six-part series.
Tags: amplpy, ampl, mip, facility-location
Author: Gyorgy Matyasfalvi (15 notebooks) <gyorgy@ampl.com>

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

Notebooks > AMPL Development Tutorial 2/6 – Stochastic Capacitated Facility Location Problem
2_stoch_floc.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: This notebook continues our six-part series as the second installment.
Tags: amplpy, ampl, mip, stochastic, facility-location
Author: Gyorgy Matyasfalvi (15 notebooks) <gyorgy@ampl.com>

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

Notebooks > 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.
Tags: amplpy, ampl, mip, stochastic, facility-location, benders, decomposition
Author: Gyorgy Matyasfalvi (15 notebooks) <gyorgy@ampl.com>

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

Notebooks > 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.
Tags: amplpy, ampl, mip, stochastic, facility-location, benders, decomposition
Author: Gyorgy Matyasfalvi (15 notebooks) <gyorgy@ampl.com>

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

Notebooks > 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.
Tags: amplpy, ampl, mip, stochastic, facility-location, benders, decomposition, parallel-solves
Author: Gyorgy Matyasfalvi (15 notebooks) <gyorgy@ampl.com>

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

Notebooks > 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).
Tags: amplpy, ampl, ampls, mip, stochastic, facility-location, benders
Author: Christian Valente (1 notebook) <ccv@ampl.com>, Gyorgy Matyasfalvi (15 notebooks) <gyorgy@ampl.com>

Debugging Model Infeasibility

Notebooks > 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.
Tags: amplpy, ampl, debug, infeasibility
Author: Gyorgy Matyasfalvi (15 notebooks) <gyorgy@ampl.com>

Introduction to Linear and Integer Programming

Notebooks > 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
Tags: ampl-lecture, amplpy, ampl, introduction, linear-programming, lemonade-stand
Author: Gyorgy Matyasfalvi (15 notebooks) <gyorgy@ampl.com>

Introduction to Mathematical Optimization

Notebooks > 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
Tags: ampl-lecture, amplpy, ampl, introduction, optimization, convexity, unconstrained
Author: Gyorgy Matyasfalvi (15 notebooks) <gyorgy@ampl.com>

Network Linear Programs

Notebooks > 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
Tags: ampl-lecture, amplpy, ampl, introduction, linear-programming, max-flow, shortest-path
Author: Gyorgy Matyasfalvi (15 notebooks) <gyorgy@ampl.com>

Production Model

Notebooks > 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
Tags: ampl-lecture, amplpy, ampl, introduction, linear-programming, sets, indexing, lemonade-stand
Author: Gyorgy Matyasfalvi (15 notebooks) <gyorgy@ampl.com>

Solving simple stochastic optimization problems with AMPL

Notebooks > 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
Tags: ampl, amplpy, stochastic-optimization, sample-average-approximation, risk-measures
Author: Nicolau Santos (3 notebooks) <nfbvs@ampl.com>

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