# ampl#

## AMPL - solve multiple models in parallel#

Description: Solve multiple AMPL models in parallel in Python with amplpy and the multiprocessing modules.

Author: Nicolau Santos (3 notebooks) <nfbvs@ampl.com>

## AMPL - spreadsheet handling with amplxl#

Description: Basic example of reading/writing data into/from a .xlsx spreadsheet with amplxl

Author: Nicolau Santos (3 notebooks) <nfbvs@ampl.com>

## AMPL Development Tutorial 1/6 – Capacitated Facility Location Problem#

Description: This notebook marks the beginning of a six-part series.

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

Description: This notebook continues our six-part series as the second installment.

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

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#

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#

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

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*#

Description: This concluding notebook in our six-part series delves into enhancing the efficiency of our decomposition algorithm by utilizing

**AMPL Solver Libraries**(*ampls*).## Debugging Model Infeasibility#

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#

Description: Basic introduction to linear programming and AMPL via a lemonade stand example

## Introduction to Mathematical Optimization#

Description: Basic introduction to optimization and AMPL via unconstrained optimization

## Network Linear Programs#

Description: Basic introduction to network linear programms and AMPL via max flow and shortest path problems

## Optimal Power Flow with AMPL and Python - Bus Injection Model (BIM)#

Description: Optimal Power Flow

Author: Nicolau Santos (5 notebooks) <nicolau@ampl.com>

## Optimal Power Flow with AMPL and Python - Bus Injection Model (BIM) with controllable-phase shifting transformers and tap-changing transformers#

## Optimal Power Flow with AMPL and Python - DC Power Flow#

Description: Optimal Power Flow

Author: Nicolau Santos (5 notebooks) <nicolau@ampl.com>

## Optimal Power Flow with AMPL and Python - conventional Power Flow#

Description: Optimal Power Flow

Author: Nicolau Santos (5 notebooks) <nicolau@ampl.com>

## Optimal Power Flow with AMPL and Python - data management#

Description: Optimal Power Flow with AMPL, Python and amplpy

Author: Nicolau Santos (5 notebooks) <nicolau@ampl.com>

## Optimization of Reinforced Concrete Production and Shipment: A Conveyor-Based Manufacturing and Curing Model#

## Production Model#

Description: Basic introduction to AMPL’s indexed entities and the Pygwalker Python package via a lemonade stand example

## Project management: Minimizing the cost of implementing an investment project, taking into account the costs and risks of completing tasks and penalties for late fulfillment of obligations.#

## Solving simple stochastic optimization problems with AMPL#

Description: Examples of the Sample Average Approximation method and risk measures in AMPL

Author: Nicolau Santos (3 notebooks) <nfbvs@ampl.com>