PyJobShop: Solving scheduling problems with constraint programming in Python

TL;DR

PyJobShop is an open-source Python library that simplifies modeling and solving various scheduling problems using constraint programming, integrating leading solvers and enabling large-scale benchmarking.

Contribution

It introduces PyJobShop, a user-friendly, open-source Python library that supports multiple scheduling problem variants and integrates top constraint programming solvers.

Findings

CP Optimizer outperforms on large-scale permutation problems

OR-Tools is competitive and fully open-source

PyJobShop enables large-scale benchmarking of scheduling solvers

Abstract

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.