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Evacuation Planning for Disaster Preparedness: An Adaptive Robust Optimization Approach — arXiv:2608.04225

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.04225
License (as archived): CC0-1.0
Archived: 2026-10-31T11:37:54.389Z
SHA-256 of the archived text: 7daeb2319d95f4930f9b013d3b60b791aaabf3815b9602596f949042b14d72b8
Stable URL of this page: https://metraipolis.com/documento/dc_d75eb83ffacd

How to cite

Evacuation Planning for Disaster Preparedness: An Adaptive Robust Optimization Approach — arXiv:2608.04225 — arXiv (en), https://arxiv.org/abs/2608.04225 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_d75eb83ffacd (Metraipolis archive dc_d75eb83ffacd, sha256 7daeb2319d95f4930f9b013d3b60b791aaabf3815b9602596f949042b14d72b8)

BibTeX

@misc{dcd75eb83ffacd,
  title = {Evacuation Planning for Disaster Preparedness: An Adaptive Robust Optimization Approach — arXiv:2608.04225},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.04225},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_d75eb83ffacd; sha256 7daeb2319d95f4930f9b013d3b60b791aaabf3815b9602596f949042b14d72b8},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.04225. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Evacuation planning for disaster preparedness requires making critical decisions under uncertainty before the number and spatial distribution of evacuees are known, including shelter location, evacuation route assignment, and relief supply prepositioning. Because these decisions are highly interdependent, planners must balance the competing objectives of maximizing relief demand coverage and minimizing evacuation time. We propose, to our knowledge, the first adaptive robust evacuation planning model to jointly optimize shelter locations, evacuation route assignments, relief supply prepositioning, and post-disaster relief item distribution. The model minimizes the worst-case weighted sum of unmet demand for relief items across shelters and the congestion-dependent evacuation time. We characterize theoretical complexity drivers of the resulting problem with mixed-integer recourse and develop a partition-and-bound algorithm that maintains tractability by selectively partitioning only the most critical subpartition of the uncertainty set while producing strong upper and lower bounds. To quantify the value of centralized route planning, we also formulate a user route choice alternative in which evacuees choose among acceptable routes. Computational experiments quantify the value of centralized route planning, which reduces worst-case unmet demand and evacuation time by up to 90.6\% and 79.3\%, respectively, relative to decentralized user route choice. Adaptive post-disaster supply redistribution further improves relief demand coverage. Coordination between evacuation routing and relief distribution creates substantial operational value under uncertainty. Centralized route planning primarily mitigates congestion by coordinating evacuee flows across shelters, whereas adaptive redistribution primarily improves relief demand coverage when relief supplies are scarce or inflexibly prepositioned.

Tema degli esploratori: matematica e informatica teorica (retro-catalogo arXiv: annunci del 2026-08-06 in math.OC).
Categorie arXiv: Optimization and Control (math.OC).
Pagina del lavoro: https://arxiv.org/abs/2608.04225 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-31T11:28:34.323Z dalla pagina https://arxiv.org/catchup/math.OC/2026-08-06?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).