Benchmarking Constraint Programming software: Insights from the Job Shop Scheduling Problem (#1134)
Read ArticleDate of Conference
July 15-17, 2026
Published In
"Engineering without Borders: Artificial Intelligence, Knowledge, Innovation, and Alliances for a Future from the Americas"
Location of Conference
Santiago (Chile)
Authors
Yuraszeck, Francisco
Rossit, Daniel Alejandro
Milović, Milenko
Córdova, Alejandro
Olivares, Gabriel
Abstract
In this article, we benchmark three popular constraint programming (CP) solvers for the job shop scheduling problem (JSSP) under identical hardware and computation-time conditions, with the objective of minimizing the makespan. For evaluation purposes, we use 80 classic Taillard instances. Overall, CP Optimizer proved to be the most competitive solver, demonstrating optimality in 38 instances, despite a slightly higher average optimality gap (3.06%). OR-Tools followed closely, achieving a marginally smaller average gap of 2.86%, proving optimality in 23 instances, and consistently producing competitive lower bounds. In third place, Hexaly exhibited improved performance as the instance size increased.