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Dynamic Multi-Depot Vehicle Routing with Online Requests: Event-Driven Transformer--DRL and Rolling-Horizon Benchmarking
A new arXiv preprint introduces an event-driven Transformer–DRL framework for dynamic multi-depot vehicle routing with online requests, benchmarking it against classical heuristics and rolling-horizon optimization — finding no method dominates across all metrics and the strongest heuristic (nearest feasible) outperformed learned policies on key objectives.
Aug 17, 2026
Vehicle routing problem using deep reinforcement learning - A case study about truck planning in the industry
A new arXiv preprint presents a deep reinforcement learning (DRL) approach to vehicle routing optimization across three industrial trucking use cases, reporting over 10% total cost reduction versus baseline methods.
Aug 10, 2026