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CD Lab - ARTIS
Christian Doppler Laboratory for Artificial Intelligence and Optimization for Planning and Scheduling

ICAPS 2024 Tutorial

AI Techniques for Solving Scheduling Problems

Scheduling problems arise in various areas, including business, engineering, healthcare, and others. In this tutorial, we will first present several scheduling problems and case studies from various application domains, such as project scheduling, production planning and scheduling, employee scheduling, and timetabling. We will then provide an overview of different AI methods for solving such problems. The topics covered will include solver-independent modeling, constraint programming, metaheuristic methods, and hybrid techniques. In the second part of the tutorial, we will discuss methods that use machine learning techniques for automatic algorithm selection and heuristic algorithm design. We will demonstrate the application of these techniques in several real-world domains.

Outline

The topics of this tutorial include:

  • Scheduling Problems: Case studies
  • Solution techniques
  • Solver-independent modelling
  • Constraint programming
  • Metaheuristic techniques
  • Hybrid methods
  • Automated algorithm selection and instance space analysis
  • Automated algorithm design/Hyper-heuristics
  • Industrial applications
  • Future challenges

Tutorial Slides

You can download the slides for this tutorial here: ICAPS_2024_tutorial.pdf

Length of the tutorial

  • Half-day

A short CV of the proposers

Nysret Musliu is an Associate Professor and the Head of the Christian Doppler Laboratory for AI and Optimization for Planning and Scheduling at TU Wien. His research focuses on problem solving and search in artificial intelligence, scheduling and timetabling, application of machine learning in optimization, and engineering of intelligent systems. He was Conference Chair of CPAIOR 2021, Conference/PC Co-Chair of CPAIOR 2020 and Conference/PC Co-Chair of PATAT 2018, and he is a steering committee member of PATAT conference series. He has lead several research projects funded by FWF, Christian Doppler Research Association, FFG, and several companies.

Lucas Kletzander is a postdoctoral researcher in the research unit Databases and AI, and Christian Doppler Laboratory for AI and Optimization for Planning and Scheduling, TU Wien. He did his PhD on automated solution methods for personnel scheduling problems. Currently, he works on complex real-life scheduling problems using exact, heuristic and hybrid methods and automated algorithm selection and configuration.

Florian Mischek is a postdoctoral researcher in the Christian Doppler Laboratory for AI and Optimization for Planning and Scheduling, research unit Databases and AI, TU Wien. He did his PhD on advanced automated project scheduling approaches for industrial test laboratories. Currently, he is working on multi-objective and explainable scheduling, as well as hyper-heuristics.

List of publications (selection)

The complete list of recent publications can be found here: https://cdlab-artis.dbai.tuwien.ac.at/publications/ , https://dblp.org/pid/64/493.html

  1. 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, 14(1): 3:1-3:27 (2023). https://dl.acm.org/doi/10.1145/3546871
  2. Lucas Kletzander, Nysret Musliu. Large-State Reinforcement Learning for Hyper-Heuristics. Proceedings of the AAAI Conference on Artificial Intelligence, 37(10), 12444-12452. (2023)
  3. Florian Mischek, Nysret Musliu. Reinforcement learning for cross-domain hyper-heuristics. IJCAI 2022: 4793-4799. DOI: https://doi.org/10.24963/ijcai.2022/664
  4. Lucas Kletzander and Nysret Musliu. Hyper-heuristics for Personnel Scheduling Domains. ICAPS 2022: 462-470. This paper won the Best Industry and Applications Track Paper Award. DOI: https://doi.org/10.1609/icaps.v32i1.19832
  5. Marie-Louise Lackner, Christoph Mrkvicka, Nysret Musliu, Daniel Walkiewicz, Felix Winter: Exact methods for the Oven Scheduling Problem. Constraints An Int. J. 28(2): 320-361 (2023)
  6. Florian Mischek, Nysret Musliu, Andrea Schaerf: Local search approaches for the test laboratory scheduling problem with variable task grouping. J. Sched. 26(5): 457-477 (2023)
  7. Arnaud De Coster, Nysret Musliu, Andrea Schaerf, Johannes Schoisswohl, Kate Smith-Miles: Algorithm selection and instance space analysis for curriculum-based course timetabling. J. Sched. 25(1): 35-58 (2022)
  8. Lucas Kletzander, Nysret Musliu: Dynamic Weight Setting for Personnel Scheduling with Many Objectives. ICAPS 2023: 509-517
  9. Lucas Kletzander, Nysret Musliu, Kate Smith-Miles: Instance space analysis for a personnel scheduling problem. Ann. Math. Artif. Intell. 89(7): 617-637 (2021)
  10. Lucas Kletzander, Nysret Musliu, Pascal Van Hentenryck: Branch and Price for Bus Driver Scheduling with Complex Break Constraints. AAAI 2021: 11853-11861
  11. Florian Mischek, Nysret Musliu: A local search framework for industrial test laboratory scheduling. Ann. Oper. Res. 302(2): 533-562 (2021)
  12. Martin Josef Geiger, Lucas Kletzander, Nysret Musliu: Solving the Torpedo Scheduling Problem. Journal of Artificial Intelligence Research. Vol 66: 1-32, 2019.
  13. Lucas Kletzander, Nysret Musliu. Solving the general employee scheduling problem. Computers and Operations Research, Volume 113, January 2020. https://doi.org/10.1016/j.cor.2019.104794
  14. Lucas Kletzander, Nysret Musliu , Johannes Gärtner, Thomas Krennwallner, Werner Schafhauser: Exact Methods for Extended Rotating Workforce Scheduling Problems. ICAPS 2019: 519-527
  15. Michael Abseher, Nysret Musliu and Stefan Woltran. Improving the Efficiency of Dynamic Programming on Tree Decompositions via Machine Learning. Journal of Artificial Intelligence Research, Volume 58, pages 1-30, 2017.