Learning to Select Promising Initial Solutions for Large Neighborhood Search-Based Multi-Agent Path Finding

Abstract

Full Citation:

Marc Huber, Günther R. Raidl, Christian Blum. Learning to Select Promising Initial Solutions for Large Neighborhood Search-Based Multi-Agent Path Finding. Computer Aided Systems Theory – EUROCAST 2024 (Alexis Quesada-Arencibia, Michael Affenzeller, Roberto Moreno-Díaz, eds.), volume 15172 of LNCS, pages 236-250, 2025, Springer.

Günther Raidl

Günther Raidl is a Professor at the Algorithms and Complexity Group.