Reducing the cost of humanitarian operations through disaster preparation and preparedness
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DOI: 10.1007/s10479-017-2587-z
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Cited by:
- Guo Fuli & Cyril Foropon & Ma Xin, 2022. "Reducing carbon emissions in humanitarian supply chain: the role of decision making and coordination," Annals of Operations Research, Springer, vol. 319(1), pages 355-377, December.
- Liang, Siqi & Bai, Xuejie & Li, Yongli & Xin, Hening, 2023. "Model and solution of sustainable bi-level emergency commodity allocation based on type-2 fuzzy theory," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
- Christopher Loynes & Jamal Ouenniche & Johannes Smedt, 2022. "The detection and location estimation of disasters using Twitter and the identification of Non-Governmental Organisations using crowdsourcing," Annals of Operations Research, Springer, vol. 308(1), pages 339-371, January.
- Yanbin Chang & Yongjia Song & Burak Eksioglu, 2022. "A stochastic look-ahead approach for hurricane relief logistics operations planning under uncertainty," Annals of Operations Research, Springer, vol. 319(1), pages 1231-1263, December.
- Hasti Seraji & Reza Tavakkoli-Moghaddam & Sobhan Asian & Harpreet Kaur, 2022. "An integrative location-allocation model for humanitarian logistics with distributive injustice and dissatisfaction under uncertainty," Annals of Operations Research, Springer, vol. 319(1), pages 211-257, December.
- Peiyu Zhang & Yankui Liu & Guoqing Yang & Guoqing Zhang, 2022. "A multi-objective distributionally robust model for sustainable last mile relief network design problem," Annals of Operations Research, Springer, vol. 309(2), pages 689-730, February.
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Keywords
Humanitarian logistics; Humanitarian operations; Disaster management; Humanitarian organizations; Disaster policy;All these keywords.
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