A Constraint-Aware Generative Framework for Synthetic Origin-Destination Demand in Logistics Networks
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arXiv:2609.04345v1 Announce Type: cross Abstract: Large-scale logistics networks require synthetic data generation capabilities to support scenario-based planning under novel conditions-such as network reconfiguration and demand shocks. Existing approaches, which rely primarily on historical observ…
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- 2026-09-07 04:00 · arXiv stat.ML
A Constraint-Aware Generative Framework for Synthetic Origin-Destination Demand in Logistics Networks