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We present an algorithm to find optimal routes in a multi-modal public transportation network. Our model takes into account many realistic features such as walking between multi-modal stations, transfer times, traffic days, multiple objectives and finding connections between geographical locations rather than just source and destination stations. In order to provide useful routing directions, we consider the robustness of the provided solutions. In addition we present numerous speed up techniques that reduce both the preprocessing time and storage. Our preliminary experiments on the Sydney transit network are promising.
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Stored only when both papers are in the corpus — 20 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.