2025S

• Database Systems / 184.686 / VU

• 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 / 213563 / 213929 / 213924 / 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

• Multi-neighborhood simulated annealing for the oven scheduling problem / 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. https://doi.org/10.1016/j.cor.2025.106999
  Project: ARTIS (2017–2025)
• Solving the Employee Task Distribution Problem with Multiple Objectives / 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).
  Project: ARTIS (2017–2025)
• Theoretical Lower Bounds for the Oven Scheduling Problem / Da Ros, F., Lackner, M.-L., & Musliu, N. (2024). Theoretical Lower Bounds for the Oven Scheduling Problem. In Proceedings of the 14th International Conference on the Practice and Theory of Automated Timetabling, PATAT 2024 (pp. 164–186).
  Project: ARTIS (2017–2025)
• Reducing Energy Consumption in Electronic Component Manufacturing through Large Neighborhood Search / Da Ros, F., Di Gaspero, L., Lackner, M.-L., & Musliu, N. (2024). Reducing Energy Consumption in Electronic Component Manufacturing through Large Neighborhood Search. In GECCO ’24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 1706–1714). https://doi.org/10.1145/3638530.3664132
  Project: ARTIS (2017–2025)
• Local Search Algorithms for the Oven Scheduling Problem / 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). https://doi.org/10.1145/3638530.3654158
  Project: ARTIS (2017–2025)
• 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 (2017–2025)
• Exact and meta-heuristic approaches for the production leveling problem / 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. https://doi.org/10.1007/s10951-022-00721-1
  Download: PDF (1.5 MB)
  Project: ARTIS (2017–2025)
• 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 (2017–2025)
• 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 (2017–2025)
• A Mathematical Analysis of an Election System Proposed by Gottlob Frege / Harrenstein, P., Lackner, M.-L., & Lackner, M. (2020). A Mathematical Analysis of an Election System Proposed by Gottlob Frege. Erkenntnis, 87(6), 2609–2644. https://doi.org/10.1007/s10670-020-00318-0
• Runs in labelled trees and mappings / Lackner, M.-L., & Panholzer, A. (2020). Runs in labelled trees and mappings. Discrete Mathematics, 343(111990), 111990. https://doi.org/10.1016/j.disc.2020.111990
• The Likelihood of Structure in Preference Profiles / Bruner, M.-L., & Lackner, M. (2014). The Likelihood of Structure in Preference Profiles. 8th Multidisciplinary Workshop on Advances in Preference Handling, Quebec, Kanada, Non-EU. http://hdl.handle.net/20.500.12708/85942
• The computational landscape of permutation patterns / Bruner, M.-L., & Lackner, M. (2013). The computational landscape of permutation patterns. arXiv. https://doi.org/10.48550/arXiv.1301.0340
  Project: FAIR (2013–2018)
• The computational landscape of permutation patterns / Bruner, M.-L., & Lackner, M. (2013). The computational landscape of permutation patterns. 11th Permutation Patterns Conference, Paris, EU. http://hdl.handle.net/20.500.12708/120423
• Permutation Pattern Matching and its Parameterized Complexity / Lackner, M., & Bruner, M.-L. (2012). Permutation Pattern Matching and its Parameterized Complexity. Conference on Computability in Europe CiE, Cambridge, Great Britain, EU. http://hdl.handle.net/20.500.12708/85363
• A Fast Algorithm for Permutation Pattern Matching Based on Alternating Runs / Lackner, M., & Bruner, M.-L. (2012). A Fast Algorithm for Permutation Pattern Matching Based on Alternating Runs. In F. Fomin & P. Kaski (Eds.), Algorithm Theory – SWAT 2012 (pp. 261–270). Springer. https://doi.org/10.1007/978-3-642-31155-0_23

• Solving the production leveling problem with memetic algorithms / Malik, P. (2023). Solving the production leveling problem with memetic algorithms [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2023.110761
  Download: PDF (1.77 MB)