Test Laboratory Scheduling

The Test Laboratory Scheduling Problem (TLSP) arises in the context of a real-world industrial test laboratory. It is related to the well-known Resource Constrained Project Scheduling Problem (RCPSP).

A detailed description of TLSP can be found in the following report: The Test Laboratory Scheduling Problem (PDF)

Data sets

All instance sets for TLSP available for download are listed here. Currently, there are two datasets, LabStructure and General. Both of these datasets are randomly generated based on real-world data. They contain instances from 5 projects and 88 time slots up to 90 projects and 782 time slots. All instances contain a base schedule with some fixed assignments and a complete grouping of tasks into jobs that has at least one feasible solution (see reference solution for each instance). More details about the instance sets and the various parameters can be found in the report linked above.

This table will be extended once additional datasets become available.

A subset of these instances was used for evaluations. It contains 15 instances each from the General and LabStructure data sets, chosen to cover the whole range of instance sizes. The instances of this set are contained in this ZIP-Archive

Real world instances

Publications

Journal

• Philipp Danzinger, Tobias Geibinger, David Janneau, Florian Mischek, Nysret Musliu and Christian Poschalko. A system for automated industrial test laboratory scheduling. ACM Transactions on Intelligent Systems and Technology (2022)
• Florian Mischek, Nysret Musliu and Andrea Schaerf. Local search approaches for the test laboratory scheduling problem with variable task grouping. Journal of Scheduling (2021)
• Tobias Geibinger, Florian Mischek and Nysret Musliu. Investigating Constraint Programming and Hybrid Methods for Real World Industrial Test Laboratory Scheduling. submitted to journal (2020)
• Florian Mischek and Nysret Musliu. A local search framework for industrial test laboratory scheduling. Annals of Operations Research (2021)

Conferences

• Florian Mischek, Nysret Musliu. Preference Explanation and Decision Support for Multi-Objective Real-World Test Laboratory Scheduling. Accepted for publication in the Proceedings of the International Conference on Automated Planning and Scheduling. ICAPS 2024
• Florian Mischek, Nysret Musliu. Leveraging problem-independent hyper-heuristics for real-world test laboratory scheduling. Proceedings of the Genetic and Evolutionary Computation Conference. GECCO 2023
• Tobias Geibinger, Florian Mischek and Nysret Musliu. Constraint Logic Programming for Real-World Test Laboratory Scheduling. AAAI 2021
• Philipp Danzinger, Tobias Geibinger, Florian Mischek and Nysret Musliu. Solving the Test Laboratory Scheduling Problem with Variable Task Grouping. Proceedings of the International Conference on Automated Planning and Scheduling - ICAPS 2020
• Florian Mischek, Nysret Musliu and Andrea Schaerf. Local Search Neighborhoods for Industrial Test Laboratory Scheduling with Flexible Grouping. accepted at PATAT2020
• Tobias Geibinger, Florian Mischek and Nysret Musliu. Investigating Constraint Programming for Real-World Industrial Test Laboratory Scheduling. Proceedings of the 16th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research - CPAIOR 2019, Thessaloniki, June 4 - 7, 2019