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The algorithms are evaluated using test instances that are generated based on real-world urban street networks. The computational results show that the proposed frameworks are more effective than a classical two-stage heuristic for solving the test instances of the LDRP. The results also indicate that, with similar computational efforts, the multi-start-based method outperforms the double-loop-based method. Moreover, the average total distance for visiting all of the collapsed buildings decreases with the increase in the detection radius. The findings and the results provide a valuable reference to emergency response agencies in the search-and-rescue actions after massive earthquakes.<\/jats:p>","DOI":"10.1007\/s13177-026-00642-9","type":"journal-article","created":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T10:44:41Z","timestamp":1775040281000},"page":"1110-1129","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Solving the Life Detector Routing Problem over a Street Network: A Multi-Start-based Approach"],"prefix":"10.1007","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8317-4193","authenticated-orcid":false,"given":"Chung-Cheng","family":"Lu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-2222-2305","authenticated-orcid":false,"given":"Yu-Shyun","family":"Chien","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shu-Hao","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,4,1]]},"reference":[{"issue":"1","key":"642_CR1","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1057\/palgrave.jors.2601652","volume":"55","author":"G Barbaroso\u01e7lu","year":"2004","unstructured":"Barbaroso\u01e7lu, G., Arda, Y.: A two-stage stochastic programming framework for transportation planning in disaster response. 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