VaP-CSMV uses a cross-semantic encoder and multi-view decoder to unify DRL solving of HFVRP variants, outperforming prior neural solvers while matching heuristics at much lower inference time and generalizing zero-shot to unseen scales.
Camp: Col- laborative attention model with profiles for vehicle routing problems
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Vehicle-as-Prompt: A Unified Deep Reinforcement Learning Framework for Heterogeneous Fleet Vehicle Routing Problem
VaP-CSMV uses a cross-semantic encoder and multi-view decoder to unify DRL solving of HFVRP variants, outperforming prior neural solvers while matching heuristics at much lower inference time and generalizing zero-shot to unseen scales.