Resources#

This section collects tutorials and example models to help you get started with cvxlab. Each tutorial walks you through the steps described in the User Guide for a specific use-case.

Tutorial directories (with supplementary modeling materials such as Jupyter Notebooks, Excel concept files, input-data files and SQLite databases) can be downloaded from the table below, so that you can run them locally on your machine.

Tutorials#

Tutorial

Description

Material

Production planning

Complete workflow for definining and solving a simple production planning under resource constraints. Step by step guide aligned with User Guide. Ideal for newbies.

link

Production planning (non-linear)

Complete workflow for definining and solving a non-linear production planning under resource constraints. Similar to previous production planning tutorial, but handling non-linearities explicitly.

link

Production planning (decomposition)

Detailed guide on reformulating and decomposing the previous non-linear production planning problem into coupled convex sub-problems solved iteratively (block Gauss–Seidel). Includes YAML snippets, hybrid table examples, convergence logs, and troubleshooting.

link

Publications#

A collection of published articles that use CVXlab for modeling and solving optimization problems.

  • Parametric life cycle assessment of carbon footprint of electricity generation from floating offshore wind farms (Ghezzi D, Rocco MV | Sustainable Energy Technology and Assessments | 2025) | Article link

How to cite CVXlab#

If you use CVXlab in your academic work, please cite the software using the following references.

APA

Rocco, M. V. (2026). CVXlab (Version 1.0.1) [Software]. Zenodo.
https://doi.org/10.5281/zenodo.20644006

BibTeX

@software{rocco_cvxlab_2026,
  author    = {Rocco, Matteo V.},
  title     = {{CVXlab}},
  version   = {1.0.1},
  year      = {2026},
  publisher = {Zenodo},
  doi       = {10.5281/zenodo.20644006},
  url       = {https://doi.org/10.5281/zenodo.20644006}
}

The Zenodo record for CVXlab is available at https://doi.org/10.5281/zenodo.20644006.