Johannes Varga

Projektass. Dipl.-Ing. / BSc BSc

Role

PreDoc Researcher
Algorithms and Complexity, E192-01

Contact

Publications

Mixed Integer Linear Programming Based Large Neighborhood Search Approaches for the Directed Feedback Vertex Set Problem / Bresich, M., Varga, J., Raidl, G. R., & Limmer, S. (2024). Mixed Integer Linear Programming Based Large Neighborhood Search Approaches for the Directed Feedback Vertex Set Problem. In B. Dorronsoro, R. Ellaia, & E.-G. Talbi (Eds.), Metaheuristics and Nature Inspired Computing : 9th International Conference, META 2023, Marrakech, Morocco, November 1–4, 2023, Revised Selected Papers (pp. 3–20). Springer. https://doi.org/10.1007/978-3-031-69257-4_1
Project: Learning to Solve Dynamic Vehicle Routing Problems (2023–2027)
Improving User Experience in Interactive Job Scheduling / Varga, J. (2024, September 12). Improving User Experience in Interactive Job Scheduling [Poster Presentation]. HRI European Graduate Network (EGN) Symposium, Offenbach, Germany.
Project: Cooperative Personnel Scheduling (2022–2026)
Scheduling jobs using queries to interactively learn human availability times / Varga, J., Raidl, G. R., Rönnberg, E., & Rodemann, T. (2024). Scheduling jobs using queries to interactively learn human availability times. COMPUTERS & OPERATIONS RESEARCH, 167, Article 106648. https://doi.org/10.1016/j.cor.2024.106648
Download: Scheduling jobs using queries to interactively learn human availability times (1.05 MB)
Project: Cooperative Personnel Scheduling (2022–2026)
Learning to Predict User Replies in Interactive Job Scheduling / Varga, J. (2024, June 21). Learning to Predict User Replies in Interactive Job Scheduling [Presentation]. Weekly scientific seminar at Honda Research Institute Europe, Offenbach, Germany.
Project: Cooperative Personnel Scheduling (2022–2026)
Speeding Up Logic-Based Benders Decomposition by Strengthening Cuts with Graph Neural Networks / Varga, J., Karlsson, E., Raidl, G. R., Rönnberg, E., Lindsten, F., & Rodemann, T. (2024). Speeding Up Logic-Based Benders Decomposition by Strengthening Cuts with Graph Neural Networks. In G. Nicosia, V. Ojha, & E. La Malfa (Eds.), Machine Learning, Optimization, and Data Science : 9th International Conference, LOD 2023, Grasmere, UK, September 22–26, 2023, Revised Selected Papers, Part I (pp. 24–38). Springer. https://doi.org/10.1007/978-3-031-53969-5_3
Project: Cooperative Personnel Scheduling (2022–2026)
Large neighborhood search for electric vehicle fleet scheduling / Limmer, S., Varga, J., & Raidl, G. (2023). Large neighborhood search for electric vehicle fleet scheduling. Energies, 16(12), Article 4576. https://doi.org/10.3390/en16124576
Download: PDF (328 KB)
Interactive Job Scheduling with Partially Known Personnel Availabilities / Varga, J., Raidl, G. R., Rönnberg, E., & Rodemann, T. (2023). Interactive Job Scheduling with Partially Known Personnel Availabilities. In B. Dorronsoro, F. Chicano, G. Danoy, & E.-G. Talbi (Eds.), Optimization and Learning: 6th International Conference, OLA 2023, Malaga, Spain, May 3–5, 2023, Proceedings (pp. 236–247). Springer. https://doi.org/10.1007/978-3-031-34020-8_18
An Evolutionary Approach for Scheduling a Fleet of Shared Electric Vehicles / Limmer, S., Varga, J., & Raidl, G. R. (2023). An Evolutionary Approach for Scheduling a Fleet of Shared Electric Vehicles. In J. G. M. Correia, S. Smith, & R. Qaddoura (Eds.), Applications of Evolutionary Computation : 26th European Conference, EvoApplications 2023, Held as Part of EvoStar 2023, Brno, Czech Republic, April 12–14, 2023, Proceedings (pp. 3–18). Springer. https://doi.org/10.1007/978-3-031-30229-9_1
Computational Methods for Scheduling the Charging and Assignment of an On-Site Shared Electric Vehicle Fleet / Varga, J., Raidl, G., & Limmer, S. (2022). Computational Methods for Scheduling the Charging and Assignment of an On-Site Shared Electric Vehicle Fleet. IEEE Access, 10, 105786–105806. https://doi.org/10.1109/ACCESS.2022.3210168
Download: PDF (2.25 MB)
Computational Methods for fleet scheduling in E-mobility / Varga, J. (2021). Computational Methods for fleet scheduling in E-mobility [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2021.87627
Download: PDF (1.26 MB)

Supervisions

Graph Neural Networks Meet Local Search for the Weighted Total Domination Problem / Simunics, A. (2024). Graph Neural Networks Meet Local Search for the Weighted Total Domination Problem [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2024.108221
Download: PDF (3.65 MB)
Hybrid metaheuristics based on large neighborhood search and mixed integer linear programming for the directed feedback vertex set problem / Bresich, M. (2023). Hybrid metaheuristics based on large neighborhood search and mixed integer linear programming for the directed feedback vertex set problem [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2023.102404
Download: PDF (1.66 MB)