TU Wien Informatics

20 Years

Role

2023W

2024S

 

2023

  • Exact methods for the Oven Scheduling Problem / Lackner, M.-L., Mrkvicka, C., Musliu, N., Walkiewicz, D., & Winter, F. (2023). Exact methods for the Oven Scheduling Problem. Constraints, 28(2), 320–361. https://doi.org/10.1007/s10601-023-09347-2
    Download: PDF (731 KB)
    Project: ARTIS (2017–2024)

2022

2021

  • Automated scheduling for automotive supplier paint shops and teeth manufacturing / Winter, F. (2021). Automated scheduling for automotive supplier paint shops and teeth manufacturing [Dissertation, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2022.100623
    Download: PDF (1.7 MB)
  • Automated Production Scheduling for Artificial Teeth Manufacturing / 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). http://hdl.handle.net/20.500.12708/58583
    Project: ARTIS (2017–2024)
  • Exact and metaheuristic approaches for unrelated parallel machine scheduling / 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. https://doi.org/10.1007/s10951-021-00714-6
    Project: ARTIS (2017–2024)
  • A large neighborhood search approach for the paint shop scheduling problem / Winter, F., & Musliu, N. (2021). A large neighborhood search approach for the paint shop scheduling problem. Journal of Scheduling, 25(4), 453–475. https://doi.org/10.1007/s10951-021-00713-7
    Project: ARTIS (2017–2024)
  • Constraint-based Scheduling for Paint Shops in the Automotive Supply Industry / 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. https://doi.org/10.1145/3430710
    Project: ARTIS (2017–2024)
  • Solving the paintshop scheduling problem with memetic algorithms / 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, EU. https://doi.org/10.1145/3449639.3459375
    Project: ARTIS (2017–2024)
  • Automated configuration of parallel machine dispatching rules by machine learning / 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, EU. https://doi.org/10.1145/3449726.3459541
    Project: ARTIS (2017–2024)
  • 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 (2017–2024)
  • Minimizing Cumulative Batch Processing Time for an Industrial Oven Scheduling Problem / 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). https://doi.org/10.4230/LIPIcs.CP.2021.37
    Project: ARTIS (2017–2024)

2020

  • Explaining Propagators for String Edit Distance Constraints / 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). https://doi.org/10.1609/aaai.v34i02.5530
    Project: ARTIS (2017–2024)

2019

2018

2017

2016