{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T11:51:31Z","timestamp":1776858691139,"version":"3.51.2"},"reference-count":43,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T00:00:00Z","timestamp":1776816000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Humanities and Social Sciences Foundation of the Ministry of Education of China","award":["24YJCZH247"],"award-info":[{"award-number":["24YJCZH247"]}]},{"name":"Humanities and Social Sciences Foundation of the Ministry of Education of China","award":["22YJCZH153"],"award-info":[{"award-number":["22YJCZH153"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>Urban transportation systems are facing increasingly severe threats from extreme weather events such as rainstorms, which can trigger cascading failures and lead to regional traffic paralysis. The strategic location of emergency facilities to enhance system resilience has emerged as a critical proactive prevention strategy. This study proposes a multi-objective hierarchical coverage location model that integrates point and flow demands to improve the resilience of urban road traffic systems under rainstorm conditions. First, the resilience risk levels of road nodes were quantified using an entropy-weighted TOPSIS method that combines topological attributes, traffic flow performance, and indirect propagation intensity. Second, a flow-capturing mechanism was introduced to address the dynamic rescue demands of stranded vehicles in motion, enabling the pre-positioning of \u201csafe havens\u201d along critical travel routes. The model balances two objectives: maximizing the resilience risk value of the covered demands and minimizing facility construction costs. A case study was conducted in Jianghan District, Wuhan, a flood-prone area, and the NSGA-II algorithm was employed to solve the multi-objective optimization problem. The results demonstrate that the proposed model significantly outperforms traditional single-demand location models in terms of coverage effectiveness and cost efficiency, achieving improvements in resilience risk coverage of up to 311.6% and cost reductions of up to 63.6%. This study provides a systems science perspective for pre-disaster emergency resource allocation, shifting the paradigm from infrastructure-centric protection to human-centered rescue.<\/jats:p>","DOI":"10.3390\/systems14050454","type":"journal-article","created":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T10:38:14Z","timestamp":1776854294000},"page":"454","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi-Objective Emergency Facility Locations Considering Point-Flow Integration Under Rainstorm Environments"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1543-5790","authenticated-orcid":false,"given":"Chao","family":"Sun","sequence":"first","affiliation":[{"name":"School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huixian","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaona","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8737-2936","authenticated-orcid":false,"given":"Jie","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Transportation, Southeast University, Nanjing 210096, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,22]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"A review of transportation infrastructure resilience research from the perspective of urban flooding","volume":"24","author":"Xiong","year":"2024","journal-title":"J. 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