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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.16149 |
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| _version_ | 1866914568520859648 |
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| author | Katkalo, Denys Rohovyi, Andrii Walsh, Toby |
| author_facet | Katkalo, Denys Rohovyi, Andrii Walsh, Toby |
| contents | State-of-the-art multimodal journey-planning algorithms, such as ULTRA, have recently been adapted to account for delays. In this work, we extend this approach to be more memory-efficient, faster, and accurate. We also adapt this framework to other state-of-the-art algorithms, like CSA and RAPTOR. We demonstrate a speedup of 1.9-4.2x over existing algorithms in the single-objective search (earliest arrival time). In the bicriteria setting, we achieve competitive speedup results but greater accuracy. We also find that our method scales much better as the delay buffer Delta increases. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_16149 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Fast and Memory Efficient Multimodal Journey Planning with Delays Katkalo, Denys Rohovyi, Andrii Walsh, Toby Data Structures and Algorithms State-of-the-art multimodal journey-planning algorithms, such as ULTRA, have recently been adapted to account for delays. In this work, we extend this approach to be more memory-efficient, faster, and accurate. We also adapt this framework to other state-of-the-art algorithms, like CSA and RAPTOR. We demonstrate a speedup of 1.9-4.2x over existing algorithms in the single-objective search (earliest arrival time). In the bicriteria setting, we achieve competitive speedup results but greater accuracy. We also find that our method scales much better as the delay buffer Delta increases. |
| title | Fast and Memory Efficient Multimodal Journey Planning with Delays |
| topic | Data Structures and Algorithms |
| url | https://arxiv.org/abs/2604.16149 |