# Modules¶

## Modules available¶

AMPL and all Solvers are now available as Python Packages. List of modules available:

Open-source:

`highs`

,`cbc`

,`coin`

(includes: CBC, Couenne, Ipopt, Bonmin),`open`

(includes all open-source solvers)NEOS Server:

`gokestrel`

(kestrel client)Commercial solvers:

`baron`

,`conopt`

,`copt`

,`cplex`

,`gurobi`

,`knitro`

,`lgo`

,`lindoglobal`

,`loqo`

,`minos`

,`mosek`

,`octeract`

,`snopt`

,`xpress`

AMPL Plugins:

`amplgsl`

(amplgsl docs),`plugins`

(amplplugins docs)

Note

On Google Colab there is a default AMPL Community
Edition license that gives you **unlimited access to AMPL
with open-source solvers** (e.g., HiGHS, CBC, Couenne, Ipopt, Bonmin)
or with commercial solvers from the NEOS Server as described in Kestrel documentation.

In the list `modules`

you need to include
`"gokestrel"`

to use the kestrel driver;
`"highs"`

for the HiGHS solver;
`"coin"`

for the COIN-OR solvers.
To use other commercial solvers, your license needs to include the commercial solver (e.g., an AMPL CE commercial solver trial).

```
# Install dependencies
%pip install -q amplpy
```

```
# Google Colab & Kaggle integration
from amplpy import AMPL, ampl_notebook
ampl = ampl_notebook(
modules=["gurobi", "coin", "highs", "gokestrel"], # modules to install
license_uuid="default", # license to use
) # instantiate AMPL object and register magics
```

Learn more: [AMPL and Solvers modules] [Solver docs]

## Notebooks grouped by modules¶

- cbc (5 notebooks)
- coin (21 notebooks)
- Book Example: Economic equilibria
- Book Example: Transshipment problem
- Book Example: diet
- Book Example: prod
- Book Example: steel
- Book Example: transp
- CP-style scheduling model with the
*numberof*operator, solved by a MIP solver - Capacity expansion of power generation
- Diet lecture
- Diet model with Google Sheets
- Google Hashcode 2022
- Hydrothermal Scheduling Problem with Conic Programming
- Logistic Regression with amplpy
- Multicommodity transportation problem
- Nonlinear transportation model
- Nonlinear transportation problem example
- Optimization Methods in Finance: Chapter 3
- Production model
- Steel industry problem
- Transportation problem
- Travelling Salesman Problem with subtour elimination

- cplex (3 notebooks)
- gcg (2 notebooks)
- gurobi (22 notebooks)
- AMPL Bin Packing Problem with GCG
- AMPL Christmas Model created by ChatGPT
- AMPL Development Tutorial 6/6 – Implementing Benders Decomposition with
*ampls* - Aircrew trainee scheduling with seniority constraints
- Book Example: Economic equilibria
- Containers scheduling
- Employee Scheduling Optimization
- Financial Portfolio Optimization with amplpy
- Introduction to Linear and Integer Programming
- Introduction to Mathematical Optimization
- Jupyter Notebook Integration
- NFL Team Rating
- Network Linear Programs
- Network design with redundancy
- Optimize your Christmas Tree to Global Optimality
- Pattern Enumeration
- Pattern Generation
- Production Model
- Robust Linear Programming with Ellipsoidal Uncertainty
- Roll Cutting - Revision 1 & 2
- Scheduling Multipurpose Batch Processes using State-Task Networks in Python
- amplpy setup & Quick Start

- highs (30 notebooks)
- AMPL - solve multiple models in parallel
- AMPL - spreadsheet handling with amplxl
- AMPL Bin Packing Problem with GCG
- AMPL Christmas Model created by ChatGPT
- AMPL Model Colaboratory Template
- Aircrew trainee scheduling with seniority constraints
- CP-style scheduling model with the
*numberof*operator, solved by a MIP solver - Containers scheduling
- Dual-Donor Organ Exchange problem
- Dynamic routing example
- Employee Scheduling Optimization
- Hospitals-Residents MIP
- Labs scheduling
- N-Queens
- Network design with redundancy
- Oil refinery production optimization
- Oil refinery production optimization (+PowerBI)
- Oil refinery production optimization (ampl-only version)
- Plot feasible region
- Quick Start using Pandas dataframes
- Quick Start using lists and dictionaries
- Scheduling Multipurpose Batch Processes using State-Task Networks in Python
- Simple sudoku solver using logical constraints (with GUI)
- Solution check: discontinuous objective function
- Solving a nonogram puzzle
- Solving simple stochastic optimization problems with AMPL
- Sudoku Generator
- Unit Commitment for Electrical Power Generation
- VPSolver: Cutting & Packing Problems
- Warehouse location and transport

- knitro (1 notebook)
- mosek (3 notebooks)
- open (14 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
- AMPL Development Tutorial 4/6 – Benders Decomposition via PYTHON scripting
- AMPL Development Tutorial 5/6 – Parallelizing Subproblem Solves in Benders Decomposition
- Debugging Model Infeasibility
- Introduction to Linear and Integer Programming
- Introduction to Mathematical Optimization
- Largest small polygon
- Magic sequences
- Network Linear Programs
- P-Median problem
- Production Model
- Supply chain network

- plugins (1 notebook)
- scip (1 notebook)