# PyJobShop: Solving scheduling problems with constraint programming in Python

arXiv: https://arxiv.org/abs/2502.13483 · HTML: https://mlsanity.com/paper/2502.13483/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Feb 2025.

## Built on by (most cited first, 1 of 1)

- [APEX: An Extensible Model for Agent-Assisted Production Scheduling](https://mlsanity.com/paper/2609.33430/) (2026)

## Abstract (arXiv)

This paper presents PyJobShop, an open-source Python library for solving scheduling problems with constraint programming. PyJobShop provides an easy-to-use modeling interface that supports a wide variety of scheduling problems, including well-known variants such as the flexible job shop problem and the resource-constrained project scheduling problem. PyJobShop integrates two state-of-the-art constraint programming solvers: Google's OR-Tools CP-SAT and IBM ILOG's CP Optimizer. We leverage PyJobShop to conduct large-scale numerical experiments on more than 9,000 benchmark instances from the machine scheduling and project scheduling literature, comparing the performance of OR-Tools and CP Optimizer. While CP Optimizer performs better on permutation scheduling and large-scale problems, OR-Tools is highly competitive on job shop scheduling and project scheduling problems--while also being fully open-source. By providing an accessible and tested implementation of constraint programming for scheduling, we hope that PyJobShop will enable researchers and practitioners to use constraint programming for real-world scheduling problems.