@misc {pub6668,
	title = {Approaching the Dynamic Electric Autonomous Dial-a-Ride Problem with Large Neighborhood Search and Reinforcement Learning},
	author = {Laurenz Tomandl AND Maria Bresich AND Guenther Raidl AND Yi Mei AND Steffen Limmer AND Tobias Rodemann},
	year = {2026},
	month = {July},
	abstract = {The Dynamic Electric Autonomous Dial-a-Ride Problem addresses shared real-time passenger transport from request-specific origins to destinations. Large Neighborhood Search (LNS) heuristics achieve state-of-the-art results for the static variant of this problem in which all information is given upfront. We extend this framework to the dynamic setting by controlling waiting times and the priorization of charging with a neural network trained by reinforcement learning. Experimental results show that our new approach consistently outperforms a myopic LNS and a Genetic Programming Hyper-Heuristic.},
	publisher = { None (presentation only)},
	booktitle = {The 24th Conference of the International Federation of Operational Research Societies (IFORS) 2026}
}