2024W

• Bachelor Thesis / 184.691 / PR
• Project in Computer Science 1 / 192.021 / PR
• Project in Computer Science 2 / 192.022 / PR
• Theoretical Computer Science / 192.017 / VU

2025S

• Bachelor Thesis / 184.691 / PR
• Database Systems / 184.686 / VU
• Problem Solving and Search in Artificial Intelligence / 181.190 / VU
• Project in Computer Science 1 / 192.021 / PR
• Project in Computer Science 2 / 192.022 / PR

• CD Laboratory for Artificial Intelligence and Optimization for Planning and Scheduling
  2017 – 2025 / Christian Doppler Research Association (CDG)
  Publications: 136808 / 139849 / 138379 / 138399 / 138400 / 138528 / 138530 / 144345 / 142199 / 142211 / 142210 / 142193 / 141227 / 141228 / 143220 / 143222 / 190688 / 191173 / 193566 / 192686 / 192678 / 203673 / 204355 / 209771 / 209950 / 209926 / 209911 / 209932 / 208556 / 209917 / 210249 / 208780 / 210368 / 210992 / 24775 / 55565 / 55636 / 57470 / 57475 / 57476 / 57570 / 57572 / 57573 / 57872 / 57873 / 57874 / 57876 / 57878 / 57880 / 58293 / 58340 / 58583 / 58584 / 58585 / 58586 / 58590 / 58591 / 86907 / 87083

2024

• Pareto Front Approximation Results for Bus Driver Scheduling with Complex Constraints / Frohner, N., Mugdan, E., Kletzander, L., & Musliu, N. (2024, October 20). Pareto Front Approximation Results for Bus Driver Scheduling with Complex Constraints [Conference Presentation]. Multi-Objective Decision Making Workshop at ECAI 2024, Santiago de Compostela, Spain. http://hdl.handle.net/20.500.12708/210368
  Project: ARTIS (2017–2025)
• Towards Multi-Objective Optimization for Rotating Workforce Scheduling / Mugdan, E., Frohner, N., Kletzander, L., & Musliu, N. (2024, October 20). Towards Multi-Objective Optimization for Rotating Workforce Scheduling [Conference Presentation]. Multi-Objective Decision Making Workshop at ECAI 2024, Santiago de compostela, Spain. http://hdl.handle.net/20.500.12708/208780
  Project: ARTIS (2017–2025)
• Hyper-heuristics for personnel scheduling domains / Kletzander, L., & Musliu, N. (2024). Hyper-heuristics for personnel scheduling domains. Artificial Intelligence, 334, Article 104172. https://doi.org/10.1016/j.artint.2024.104172
  Project: ARTIS (2017–2025)
• Instance Space Analysis for the Bus Driver Scheduling Problem / Mannelli Mazzoli, T., Kletzander, L., Musliu, N., & Smith-Miles, K. (2024). Instance Space Analysis for the Bus Driver Scheduling Problem. In Proceedings of the 14th International Conference on the Practice and Theory of Automated Timetabling, PATAT 2024 (pp. 20–35).
• Combining Aircraft Maintenance Routing with a Distribution Objective / Kletzander, L., Gjergji, I., & Musliu, N. (2024). Combining Aircraft Maintenance Routing with a Distribution Objective. In Proceedings of the 14th International Conference on the Practice and Theory of Automated Timetabling, PATAT 2024 (pp. 325–328).
  Project: ARTIS (2017–2025)
• AI Techniques for Solving Scheduling Problems / Musliu, N., Kletzander, L., & Mischek, F. (2024, June 3). AI Techniques for Solving Scheduling Problems [Presentation]. 34th International Conference on Automated Planning and Scheduling (ICAPS 2024), Banaff, Alberta, Canada. http://hdl.handle.net/20.500.12708/210992
  Project: ARTIS (2017–2025)
• Investigating Large Neighbourhood Search for Bus Driver Scheduling / Mazzoli, T. M., Kletzander, L., Van Hentenryck, P., & Musliu, N. (2024). Investigating Large Neighbourhood Search for Bus Driver Scheduling. In S. Bernardini & C. Muise (Eds.), Vol. 34 (2024): Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling (pp. 360–368). AAAI Press. https://doi.org/10.1609/icaps.v34i1.31495
• A Decision Support System Prototype for Automated Bus Driver Scheduling / Frohner, N., Mugdan, E., Kletzander, L., & Musliu, N. (2024). A Decision Support System Prototype for Automated Bus Driver Scheduling. In Proceedings of the 14th International Conference on the Practice and Theory of Automated Timetabling, PATAT 2024 (pp. 259–262).
  Project: ARTIS (2017–2025)

2023

• Dynamic Weight Setting for Personnel Scheduling with Many Objectives / Kletzander, L., & Musliu, N. (2023). Dynamic Weight Setting for Personnel Scheduling with Many Objectives. In S. Koenig, R. Stern, & M. Vallati (Eds.), Proceedings of the Thirty-Third International Conference on Automated  Planning and Scheduling (pp. 509–517). AAAI Press. https://doi.org/10.1609/icaps.v33i1.27231
  Download: PDF (152 KB)
  Project: ARTIS (2017–2025)
• Large-State Reinforcement Learning for Hyper-Heuristics / Kletzander, L., & Musliu, N. (2023). Large-State Reinforcement Learning for Hyper-Heuristics. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (pp. 12444–12452). AAAI Press. https://doi.org/10.1609/aaai.v37i10.26466
  Download: All rights reserved (134 KB)
  Project: ARTIS (2017–2025)

2022

• Metaheuristic algorithms for the bus driver scheduling problem with complex break constraints / Kletzander, L., Mazzoli, T. M., & Musliu, N. (2022). Metaheuristic algorithms for the bus driver scheduling problem with complex break constraints. In GECCO ’22: Proceedings of the Genetic and Evolutionary Computation Conference (pp. 232–240). https://doi.org/10.1145/3512290.3528876
• Hyper-Heuristics for Personnel Scheduling Domains / Kletzander, L., & Musliu, N. (2022). Hyper-Heuristics for Personnel Scheduling Domains. In Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling (pp. 462–470). AAAI Press. https://doi.org/10.1609/icaps.v32i1.19832
  Project: ARTIS (2017–2025)
• Automated solution methods for complex real-life personnel scheduling problems / Kletzander, L. (2022). Automated solution methods for complex real-life personnel scheduling problems [Dissertation, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2023.108382
  Download: PDF (2.79 MB)

2021

• Instance space analysis for a personnel scheduling problem / Kletzander, L., Musliu, N., & Smith-Miles, K. (2021). Instance space analysis for a personnel scheduling problem. Annals of Mathematics and Artificial Intelligence, 89(7), 617–637. https://doi.org/10.1007/s10472-020-09695-2
  Download: PDF (4.52 MB)
  Project: ARTIS (2017–2025)
• Branch and Price for Bus Driver Scheduling with Complex Break Constraints / Kletzander, L., Musliu, N., & Van Hentenryck, P. (2021). Branch and Price for Bus Driver Scheduling with Complex Break Constraints. In Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, {IAAI} 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, {EAAI} 2021, Virtual Event, February 2-9, 2021 (pp. 11853–11861). http://hdl.handle.net/20.500.12708/58590
  Project: ARTIS (2017–2025)
• Physician Scheduling During a Pandemic / Geibinger, T., Kletzander, L., Krainz, M., Mischek, F., Musliu, N., & Winter, F. (2021). Physician Scheduling During a Pandemic. In Integration of Constraint Programming, Artificial Intelligence, and Operations Research (pp. 456–465). https://doi.org/10.1007/978-3-030-78230-6_29
  Project: ARTIS (2017–2025)

2020

• Solving Large Real-Life Bus Driver Scheduling Problems with Complex Break Constraints / Kletzander, L., & Musliu, N. (2020). Solving Large Real-Life Bus Driver Scheduling Problems with Complex Break Constraints. In Proceedings of the Thirtieth International Conference on Automated Planning and Scheduling, Nancy, France, October 26-30, 2020 (pp. 421–430). http://hdl.handle.net/20.500.12708/55565
  Project: ARTIS (2017–2025)
• Solving the general employee scheduling problem / Kletzander, L., & Musliu, N. (2020). Solving the general employee scheduling problem. Computers and Operations Research, 113(104794), 104794. https://doi.org/10.1016/j.cor.2019.104794
  Project: ARTIS (2017–2025)
• Instance space analysis for a personnel scheduling problem / Kletzander, L., Musliu, N., & Smith-Miles, K. (2020). Instance space analysis for a personnel scheduling problem. Annals of Mathematics and Artificial Intelligence, 89(7), 617–637. https://doi.org/10.1007/s10472-020-09695-2
  Project: ARTIS (2017–2025)

2019

• Solving the Torpedo Scheduling Problem / Geiger, M. J., Kletzander, L., & Musliu, N. (2019). Solving the Torpedo Scheduling Problem. Journal of Artificial Intelligence Research, 66, 1–32. https://doi.org/10.1613/jair.1.11303
  Project: ARTIS (2017–2025)
• Exact Methods for Extended Rotating Workforce Scheduling Problems / Kletzander, L., Musliu, N., Gärtner, J., Krennwallner, J., & Schafhauser, W. (2019). Exact Methods for Extended Rotating Workforce Scheduling Problems. In Proceedings of the Twenty-Ninth International Conference on Automated Planning and Scheduling, {ICAPS} 2018, Berkeley, CA, USA, July 11-15, 2019 (pp. 519–527). AAAI Press. http://hdl.handle.net/20.500.12708/57873
  Project: ARTIS (2017–2025)
• Modelling and Solving the Minimum Shift Design Problem / Kletzander, L., & Musliu, N. (2019). Modelling and Solving the Minimum Shift Design Problem. In Integration of Constraint Programming, Artificial Intelligence, and Operations Research 16th International Conference, CPAIOR 2019, Thessaloniki, Greece, June 4–7, 2019, Proceedings. CPAIOR 2019 - 16th International Conference on the Integration of Constraint Programming, Artificial Intelligence and Operations Research, Thessaloniki, Greece. Springer. https://doi.org/10.1007/978-3-030-19212-9_26
  Project: ARTIS (2017–2025)
• Instance Space Analysis for a Personnel Scheduling Problem / Kletzander, L., Musliu, N., & Smith-Miles, K. (2019). Instance Space Analysis for a Personnel Scheduling Problem. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, {IJCAI} 2019 (pp. 1–8). http://hdl.handle.net/20.500.12708/57880
  Project: ARTIS (2017–2025)

2018

• A Heuristic solver framework for the general employee scheduling problem / Kletzander, L. (2018). A Heuristic solver framework for the general employee scheduling problem [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2018.51761
  Download: PDF (888 KB)
• Solving the General Employee Scheduling Problem / Kletzander, L., & Musliu, N. (2018). Solving the General Employee Scheduling Problem. In 12th International Conference on the Practice and Theory of Automated Timetabling - PATAT 2018 (pp. 1–36). http://hdl.handle.net/20.500.12708/57573
  Project: ARTIS (2017–2025)

2017

• A Multi-stage Simulated Annealing Algorithm for the Torpedo Scheduling Problem / Kletzander, L., & Musliu, N. (2017). A Multi-stage Simulated Annealing Algorithm for the Torpedo Scheduling Problem. In Integration of AI and OR Techniques in Constraint Programming (pp. 344–358). Lecture Notes in Computer Science (LNCS) / Springer. https://doi.org/10.1007/978-3-319-59776-8_28
  Project: ARTE (2012–2017)

• Why Is There No (Better) Solution? Explainability Results for the Multiobjective Rotating Workforce Scheduling Problem / Mugdan, E. S. (2025). Why Is There No (Better) Solution? Explainability Results for the Multiobjective Rotating Workforce Scheduling Problem [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2025.127865
  Download: PDF (1.86 MB)
• Cross-domain selection hyper-heuristics with deep reinforcement learning / Mayrhofer, H. (2024). Cross-domain selection hyper-heuristics with deep reinforcement learning [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2025.124798
  Download: PDF (2.6 MB)