2022W

• Bachelor Thesis / 184.691 / PR
• Data Base Systems / 184.686 / VU
• Data Modelling / 184.685 / VU
• Project in Computer Science 1 / 184.688 / PR
• Project in Computer Science 2 / 184.689 / PR

• CD Laboratory for Artificial Intelligence and Optimization for Planning and Scheduling
  2017 – 2024 / Christian Doppler Research Association (CDG) / Publications: 143666, 144274, 145912, 145932, 145933, 146062, 146064, 148760, 148767, 148780, 148786, 148794, 151216, 151217, 153181, 153183, 28044, 59343, 59414, 61264, 61269, 61270, 61364, 61366, 61367, 61667, 61668, 61669, 61671, 61673, 61675, 62088, 62136, 62379, 62380, 62381, 62382, 62386, 62387, 91681, 91858

Note: Due to the rollout of TU Wien’s new publication database, the list below may be slightly outdated. Once the migration is complete, everything will be up to date again.

• Exact and meta-heuristic approaches for the production leveling problem / Winter, F., Lackner, M.-L., Vass, J., & Musliu, N. (2022). Exact and meta-heuristic approaches for the production leveling problem. Journal of Scheduling, 25(3), 339–370. https://doi.org/10.1007/s10951-022-00721-1 / Project: ARTIS
• An Investigation of Hyper-Heuristic Approaches for Teeth Scheduling / 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. / Project: ARTIS
• A Hybrid Approach for Paint Shop Scheduling in the Automotive Supply Industry / 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). http://hdl.handle.net/20.500.12708/142193 / Project: ARTIS
• Solving an Industrial Oven Scheduling Problem with a Simulated Annealing Approach / 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). http://hdl.handle.net/20.500.12708/142210 / Project: ARTIS
• Solving the Production Leveling Problem with Order-Splitting and Resource Constraints / 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). http://hdl.handle.net/20.500.12708/142211 / Project: ARTIS
• Modeling and Solving the K-track Assignment Problem / 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. http://hdl.handle.net/20.500.12708/142199 / Project: ARTIS
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• Modeling and solving staff scheduling with partial weighted maxSAT / Winter, F., Musliu, N., & Demirovic, E. (2019). Modeling and solving staff scheduling with partial weighted maxSAT. Annals of Operations Research, 275(1), 79–99. https://doi.org/10.1007/s10479-017-2693-y
• Exact Methods for a Paint Shop Scheduling Problem from the Automotive Supply Industry / 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, EU. http://hdl.handle.net/20.500.12708/86907 / Project: ARTIS
• Solution Approaches for an Automotive Paint Shop Scheduling Problem / 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. http://hdl.handle.net/20.500.12708/57874 / Project: ARTIS
• Modeling and Solving an Automotive Paint Shop Scheduling Problem / 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). http://hdl.handle.net/20.500.12708/57476 / Project: ARTIS
• Solution-Based Phase Saving and MaxSAT for Employee Scheduling: A Computational Study / 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). http://hdl.handle.net/20.500.12708/57475 / Project: ARTIS
• Paint Shop Scheduling in the Automotive Supply Industry / 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). http://hdl.handle.net/20.500.12708/57470 / Project: ARTIS
• A Hybrid Approach for the Sudoku Problem: Using Constraint Programming in Iterated Local Search / 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. https://doi.org/10.1109/mis.2017.29 / Project: ARTE
• MaxSAT modeling and metaheuristic methods for the employee scheduling problem / Winter, F. (2016). MaxSAT modeling and metaheuristic methods for the employee scheduling problem [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2016.36862
• Modeling and solving staff scheduling with partial weighted maxSAT / 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). http://hdl.handle.net/20.500.12708/56872

Note: Due to the rollout of TU Wien’s new publication database, the list below may be slightly outdated. Once the migration is complete, everything will be up to date again.

• Solving the paintshop scheduling problem with memetic algorithms / Weintritt, W. (2020). Solving the paintshop scheduling problem with memetic algorithms [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2020.80201