Pre-positioning and real-time disaster response operations: Optimization with mobile phone location data

•Explore how mobile phone location data are applied to capture disaster information.•Link pre-positioning and real-time response operations for integrated optimization.•Propose a preparedness-response two-stage integrated stochastic programming model.•Provide management insight on mobile phone locat...

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Veröffentlicht in:	Transportation research. Part E, Logistics and transportation review Jg. 150; S. 102344
Hauptverfasser:	Wang, Jing, Cai, Jianping, Yue, Xiaohang, Suresh, Nallan C.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.06.2021
Schlagworte:	Mobile phone location data Preparedness-response integrated optimization Real-time disaster information Two-stage scenario-based stochastic programming model Real-time disaster information Mobile phone location data Two-stage scenario-based stochastic programming model Preparedness-response integrated optimization
ISSN:	1366-5545, 1878-5794
Online-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	•Explore how mobile phone location data are applied to capture disaster information.•Link pre-positioning and real-time response operations for integrated optimization.•Propose a preparedness-response two-stage integrated stochastic programming model.•Provide management insight on mobile phone location data in disaster relief field. Uncertainty of disaster information severely hinders efficiency of disaster relief operations. This paper explores how mobile phone location data are applied to capture rapidly accurate disaster information and proposes a preparedness-response two-stage scenario-based stochastic programming model with mobile phone location data for integrated pre-positioning and real-time response operation optimization. The Dantzig-Wolfe decomposition approach based on Lagrange duality and branch-and-bound algorithm are adopted to solve this model. The applicability of the model is proved via a real-world case study on the Haiti earthquake. Numerical experiments are performed to offer important managerial implications and insights in disaster management, especially for large-scale disasters.
ISSN:	1366-5545 1878-5794
DOI:	10.1016/j.tre.2021.102344