Summer 2027

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

Winter 2026

• 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

• ARTIS: CD Laboratory for Artificial Intelligence and Optimization for Planning and Scheduling
  2017 – 2025 / Christian Doppler Research Association (CDG) / Website / Publications (70)

2026

• Winter, F. (2026). A Two-Stage Constraint Programming Approach for Artificial Teeth Scheduling. In 32nd International Conference on Principles and Practice of Constraint Programming (pp. 1–23). Schloss Dagstuhl – Leibniz-Zentrum für Informatik. Peer-reviewed.
  DOI: 10.4230/LIPIcs.CP.2026.58
• Frühwirth, L., Einspieler, C., Musliu, N., Winter, F. (2026). GPMS: A Generalized Parallel Machine Scheduling Framework with Rich Temporal and Resource Constraints. In Proceedings of the Thirty-Sixth International Conference on Automated Planning and Scheduling (pp. 490–499). AAAI Press. Peer-reviewed.
  DOI: 10.1609/icaps.v36i1.42866
• Da Ros, F., Di Gaspero, L., Lackner, M.-L., Musliu, N., Winter, F. (2026). Corrigendum to “Multi-neighborhood simulated annealing for the oven scheduling problem” [Comput. Oper. Res. 177 (2025) 106999]. COMPUTERS OPERATIONS RESEARCH, 185, Article 107251. Peer-reviewed.
  DOI: 10.1016/j.cor.2025.107251 / Project: ARTIS

2025

• Nagler, F., Musliu, N., Winter, F. (2025). Solution Approaches for the Balanced Task Planning Problem. In G. Ochoa (Ed.), GECCO ’25 Companion: Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 239–242). Association for Computing Machinery. Peer-reviewed.
  DOI: 10.1145/3712255.3726682 / Project: ARTIS
• Da Ros, F., Di Gaspero, L., Lackner, M.-L., Musliu, N., Winter, F. (2025). Multi-neighborhood simulated annealing for the oven scheduling problem. COMPUTERS OPERATIONS RESEARCH, 177, Article 106999. Peer-reviewed.
  DOI: 10.1016/j.cor.2025.106999 / Project: ARTIS

2024

• Da Ros, F., Di Gaspero, L., Lackner, M.-L., Musliu, N., Winter, F. (2024). Local Search Algorithms for the Oven Scheduling Problem. In GECCO ’24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 191–194). Peer-reviewed.
  DOI: 10.1145/3638530.3654158 / Project: ARTIS
• Winter, F., Musliu, N. (2024). A Hybrid Approach for the Artificial Teeth Scheduling Problem. In Proceedings of the 14th International Conference on the Practice and Theory of Automated Timetabling, PATAT 2024 (pp. 255–258). Peer-reviewed.
  HDL: 20.500.12708/209950 / Project: ARTIS
• Horn, M., Lackner, M.-L., Mrkvicka, C., Musliu, N., Preininger, J., Winter, F. (2024). Solving the Employee Task Distribution Problem with Multiple Objectives. In Proceedings of the 14th International Conference on the Practice and Theory of Automated Timetabling, PATAT 2024 (pp. 36–51). Peer-reviewed.
  HDL: 20.500.12708/209926 / Project: ARTIS

2023

• Lackner, M.-L., Mrkvicka, C., Musliu, N., Walkiewicz, D., Winter, F. (2023). Exact methods for the Oven Scheduling Problem. Constraints, 28(2), 320–361. Peer-reviewed.
  DOI: 10.1007/s10601-023-09347-2 / Download: PDF / Project: ARTIS

2022

• Winter, F., Meiswinkel, S., Musliu, N., Walkiewicz, D. (2022). Modeling and Solving Parallel Machine Scheduling with Contamination Constraints in the Agricultural Industry. In 28th International Conference on Principles and Practice of Constraint Programming, CP 2022, July 31 to August 8, 2022, Haifa, Israel (pp. 1–18). Peer-reviewed.
  DOI: 10.4230/LIPIcs.CP.2022.41 / Download: PDF / Project: ARTIS
• Vass, J., Lackner, M.-L., Mrkvicka, C., Musliu, N., Winter, F. (2022). Exact and meta-heuristic approaches for the production leveling problem. Journal of Scheduling, 25(3), 339–370. Peer-reviewed.
  DOI: 10.1007/s10951-022-00721-1 / Download: PDF / Project: ARTIS
• Winter, F., Musliu, N. (2022). An Investigation of Hyper-Heuristic Approaches for Teeth Scheduling. In MIC 2022: 14th Metaheuristics International Conference. 14th Metaheuristics International Conference (MIC 2022), Ortigia-Syracuse, Italy. Springer. Peer-reviewed.
  HDL: 20.500.12708/144345 / Project: ARTIS
• Preininger, J., Winter, F., Musliu, N. (2022). Modeling and Solving the K-track Assignment Problem. In 14th Metaheuristics International Conference. MIC 2022 - 14th Metaheuristics International Conference, Ortigia-Syracuse, Italy. Springer. Peer-reviewed.
  HDL: 20.500.12708/142199 / Project: ARTIS
• Vass, J., Musliu, N., Winter, F. (2022). Solving the Production Leveling Problem with Order-Splitting and Resource Constraints. In Proceedings of the 13th International Conference on the Practice and Theory of Automated Timetabling (pp. 261–284). Peer-reviewed.
  HDL: 20.500.12708/142211 / Project: ARTIS
• Lackner, M.-L., Musliu, N., Winter, F. (2022). Solving an Industrial Oven Scheduling Problem with a Simulated Annealing Approach. In Proceedings of the 13th International Conference on the Practice and Theory of Automated Timetabling (pp. 115–120). Peer-reviewed.
  HDL: 20.500.12708/142210 / Project: ARTIS
• Winter, F., Musliu, N. (2022). A Hybrid Approach for Paint Shop Scheduling in the Automotive Supply Industry. In Proceedings of the 13th International Conference on the Practice and Theory of Automated Timetabling (pp. 317–320). Peer-reviewed.
  HDL: 20.500.12708/142193 / Project: ARTIS

2021

• Lackner, M.-L., Mrkvicka, C., Musliu, N., Walkiewicz, D., Winter, F. (2021). Minimizing Cumulative Batch Processing Time for an Industrial Oven Scheduling Problem. In 27th International Conference on Principles and Practice of Constraint Programming, {CP} 2021, Montpellier, France (Virtual Conference), October 25-29, 2021} (pp. 37:1-37:18). Peer-reviewed.
  DOI: 10.4230/LIPIcs.CP.2021.37 / Project: ARTIS
• Mrkvicka, C., Musliu, N., Preininger, J., Winter, F. (2021). Automated Production Scheduling for Artificial Teeth Manufacturing. In Proceedings of the Thirty-First International Conference on Automated Planning and Scheduling, {ICAPS} 2021, Guangzhou, China (virtual), August 2-13, 2021}, (pp. 500–508). Peer-reviewed.
  HDL: 20.500.12708/58583 / Project: ARTIS
• 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). Peer-reviewed.
  DOI: 10.1007/978-3-030-78230-6_29 / Project: ARTIS
• Faustmann, G., Mrkvicka, C., Musliu, N., Winter, F. (2021). Automated configuration of parallel machine dispatching rules by machine learning. In Proceedings of the Genetic and Evolutionary Computation Conference Companion. GECCO 2021 - Genetic and Evolutionary Computation Conference, Companion Volume, Lille, France. Peer-reviewed.
  DOI: 10.1145/3449726.3459541 / Project: ARTIS
• Musliu, N., Weintritt, W., Winter, F. (2021). Solving the paintshop scheduling problem with memetic algorithms. In Proceedings of the Genetic and Evolutionary Computation Conference. GECCO 2021 - Genetic and Evolutionary Computation Conference, Companion Volume, Lille, France. Peer-reviewed.
  DOI: 10.1145/3449639.3459375 / Project: ARTIS
• Winter, F., Musliu, N. (2021). Constraint-based Scheduling for Paint Shops in the Automotive Supply Industry. ACM Transactions on Intelligent Systems and Technology, 12(2), 1–25. Peer-reviewed.
  DOI: 10.1145/3430710 / Project: ARTIS
• Moser, M., Musliu, N., Schaerf, A., Winter, F. (2021). Exact and metaheuristic approaches for unrelated parallel machine scheduling. Journal of Scheduling, 25(5), 507–534. Peer-reviewed.
  DOI: 10.1007/s10951-021-00714-6 / Project: ARTIS
• Winter, F., Musliu, N. (2021). A large neighborhood search approach for the paint shop scheduling problem. Journal of Scheduling, 25(4), 453–475. Peer-reviewed.
  DOI: 10.1007/s10951-021-00713-7 / Project: ARTIS

2020

• Musliu, N., Winter, F., Stuckey, P. J. (2020). Explaining Propagators for String Edit Distance Constraints. In Proceedings of the AAAI Conference on Artificial Intelligence (pp. 1676–1683). Peer-reviewed.
  DOI: 10.1609/aaai.v34i02.5530 / Project: ARTIS

2019

• Winter, F., Musliu, N., Mrkvicka, C., Demirovic, E. (2019). Solution Approaches for an Automotive Paint Shop Scheduling Problem. In Proceedings of the Twenty-Ninth International Conference on Automated Planning and Scheduling, {ICAPS} 2019 (pp. 573–581). AAAI Press. Peer-reviewed.
  HDL: 20.500.12708/57874 / Project: ARTIS
• Demirovic, E., Musliu, N., Winter, F. (2019). Modeling and solving staff scheduling with partial weighted maxSAT. Annals of Operations Research, 275(1), 79–99. Peer-reviewed.
  DOI: 10.1007/s10479-017-2693-y

2018

• Winter, F., Musliu, N., Demirovic, E., Mrkvicka, C. (2018). Paint Shop Scheduling in the Automotive Supply Industry. In 29th European Conference on Operational Research (p. 161). Peer-reviewed.
  HDL: 20.500.12708/57470 / Project: ARTIS
• Winter, F., Musliu, N., Demirovic, E., Stuckey, P. J. (2018). Solution-Based Phase Saving and MaxSAT for Employee Scheduling: A Computational Study. In 12th International Conference on the Practice and Theory of Automated Timetabling (pp. 453–457). Peer-reviewed.
  HDL: 20.500.12708/57475 / Project: ARTIS
• Winter, F., Musliu, N., Demirovic, E., Mrkvicka, C. (2018). Modeling and Solving an Automotive Paint Shop Scheduling Problem. In 12th International Conference on the Practice and Theory of Automated Timetabling (pp. 477–480). Peer-reviewed.
  HDL: 20.500.12708/57476 / Project: ARTIS

2017

• Musliu, N., Winter, F. (2017). A Hybrid Approach for the Sudoku Problem: Using Constraint Programming in Iterated Local Search. IEEE Intelligent Systems, 32(2), 52–62. Peer-reviewed.
  DOI: 10.1109/mis.2017.29 / Project: ARTE

2016

• Demirovic, E., Musliu, N., Winter, F. (2016). Modeling and solving staff scheduling with partial weighted maxSAT. In PATAT 2016: Proceedings of the 11th International Conference of the Practice and Theory of Automated Timetabling (p. 17). Peer-reviewed.
  HDL: 20.500.12708/56872

• Winter, F., Musliu, N. (2019). Exact Methods for a Paint Shop Scheduling Problem from the Automotive Supply Industry. CPAIOR 2019 - 16th International Conference on the Integration of Constraint Programming, Artificial Intelligence and Operations Research, Thessaloniki, Greece.
  HDL: 20.500.12708/86907 / Project: ARTIS

• Moik, M. (2025). Instance space analysis and constraint programming models for unrelated parallel machine scheduling problems [Diploma Thesis, Technische Universität Wien]. reposiTUm.
  DOI: 10.34726/hss.2025.127152 / Download: PDF
• Eischer, A. M. (2024). Optimizing the cell assignment problem [Diploma Thesis, Technische Universität Wien]. reposiTUm.
  DOI: 10.34726/hss.2025.126921 / Download: PDF
• Nagler, F. (2024). Solution approaches for balanced task planning and employee task distribution [Diploma Thesis, Technische Universität Wien]. reposiTUm.
  DOI: 10.34726/hss.2025.117505 / Download: PDF
• Winter, F. (2021). Automated scheduling for automotive supplier paint shops and teeth manufacturing [Dissertation, Technische Universität Wien]. reposiTUm.
  DOI: 10.34726/hss.2022.100623 / Download: PDF
• Weintritt, W. (2020). Solving the paintshop scheduling problem with memetic algorithms [Diploma Thesis, Technische Universität Wien]. reposiTUm.
  DOI: 10.34726/hss.2020.80201 / Download: PDF
• Winter, F. (2016). MaxSAT modeling and metaheuristic methods for the employee scheduling problem [Diploma Thesis, Technische Universität Wien]. reposiTUm.
  DOI: 10.34726/hss.2016.36862 / Download: PDF