Filipe Brandão (16 notebooks)

AMPL Christmas Model created by ChatGPT

AMPL Model Colaboratory Template

colab.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Basic notebook template for the AMPL Colab repository

Diet model with Google Sheets

Financial Portfolio Optimization with amplpy

amplpyfinance_vs_amplpy.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Financial Portfolio Optimization with amplpy and amplpyfinance

Jupyter Notebook Integration

magics.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Jupyter Notebook Integration with amplpy

Logistic Regression with amplpy

Network design with redundancy

electric_grid_with_redundancy.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Design of an electricity transportation network provides enough redundancy, so that a break of one component does not prevent any user from receiving electricity. The approach also works for similar distribution networks and can potentially be used in the design of military logistic networks.

Optimize your Christmas Tree to Global Optimality

Pattern Enumeration

pattern_enumeration.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Pattern enumeration example with amplpy

Pattern Generation

pattern_generation.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Pattern generation example with amplpy

Quick Start using Pandas dataframes

pandasdiet.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Quick Start using Pandas dataframes to load and retrieve data

Quick Start using lists and dictionaries

nativediet.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Quick Start using lists and dictionaries to load and retrieve data

Roll Cutting - Revision 1 & 2

pattern_tradeoff.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Pattern tradeoff example with amplpy

Scheduling Multipurpose Batch Processes using State-Task Networks in Python

batch_processessing.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: The State-Task Network (STN) is an approach to modeling multipurpose batch process for the purpose of short term scheduling. It was first developed by Kondili, et al., in 1993, and subsequently developed and extended by others.

VPSolver: Cutting & Packing Problems

vpsolver.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: Solving cutting & packing problems using arc-flow formulations

amplpy setup & Quick Start

quickstart.ipynb Open In Colab Kaggle Gradient Open In SageMaker Studio Lab
Description: amplpy setup and quick start