Benchmarking Constraint Programming software: Insights from the Job Shop Scheduling Problem
DOI:
https://doi.org/10.18687/LACCEI2026.1.1.1134Palabras clave:
constraint programming, job shop scheduling problem, CP Optimizer, Google OR-Tools, HexalyResumen
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.
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2026-07-27
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Esta obra está bajo una Licencia Creative Commons Atribución-NoComercial-CompartirIgual 4.0 Internacional.
LACCEI conserva el copyright de todos los artículos publicados bajo los términos de su acuerdo de transferencia de copyright. Como titular del copyright, LACCEI distribuye los artículos al público bajo la Licencia Internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0 (CC BY-NC-SA 4.0).
Cómo citar
Yuraszeck, F., Rossit, D. A., Milović, M., Córdova, A., & Olivares, G. (2026). Benchmarking Constraint Programming software: Insights from the Job Shop Scheduling Problem. LACCEI, 1(14). https://doi.org/10.18687/LACCEI2026.1.1.1134