AI RESEARCH
LINC: Decoupling Local Consequence Scoring from Hidden Matching in Constructive Neural Routing
arXiv CS.LG
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ArXi:2605.06332v1 Announce Type: new Constructive neural routing solvers usually score the next action by matching a decoder context to candidate embeddings, hiding deterministic one-step consequences such as travel, waiting, slack, and capacity changes. We propose LINC (Local Inference via Normed Comparison), a decoder-side candidate decision architecture that computes these consequences explicitly. LINC uses them according to their decision role: centered relative consequences are compared by a shared linear local scorer, while feasible-set summaries modulate the decoder context.