Publications: Laurenz Tomandl

[1]

A Reinforcement Learning Guided Large Neighborhood Search for the Dynamic Electric Autonomous Dial-a-Ride Problem
Laurenz Tomandl, Maria Bresich, Günther R. Raidl, Yi, Mei, Steffen Limmer, Tobias Rodemann
Machine Learning, Optimization, and Data Science – LOD 2025 (Giuseppe Nicosia, Varunand Giesselbach, Sven Ojha, M. Panos Pardalos, Renato Umeton, La Malfa Emanuele, La Malfa Gabriele, eds.), volume 16467 of LNCS, pages 425-439, 2026, Springer.
[bibtex] [doi]

[1]	A Learning Twolevel Optimization Approach for the Demand Maximizing Battery Swapping Station Location Problem Laurenz Tomandl, Thomas Jatschka, Günther Raidl, Tobias Rodemann Computer Aided Systems Theory – EUROCAST 2024 (Alexis Quesada-Arencibia, Michael Affenzeller, Roberto Moreno-Díaz, eds.), volume 15172 of LNCS, pages 251–262, 2025, Springer. [bibtex] [doi]
[2]	Genetic Programming Hyper-Heuristic for the Dynamic Electric Dial-a-Ride Problem William Huang, Yi Mei, Günther R. Raidl, Fangfang Zhang, Laurenz Tomandl, Steffen Limmer, Mengjie Zhang, Tobias Rodemann 2025 IEEE Congress on Evolutionary Computation (CEC), pages 1-8, 2025, IEEE. [bibtex] [pdf] [doi]

[1]	A Learning Multilevel Optimization Approach for a Large Location Allocation Problem Laurenz Tomandl May 2023, Master's thesis, TU Wien, Institute of Logic and Computation. Note: supervised by G. Raidl and T. Jatschka [pdf]

[1]

A Reproducibility Study on User-centric MIR Research and Why it is Important
Peter Knees, Bruce Ferwerda, Andreas Rauber, Sebastian Strumbelj, Annabel Resch, Laurenz Tomandl, Valentin Bauer, Fung Yee Tang, Josip Bobinac, Amila Ceranic, Riad Dizdar
pages 764–771, 2022, International Society for Music Information Retrieval.
[bibtex] [pdf] [doi]