Quick recovery of emergency service facilities (ESFs) in the aftermath of large-scale disasters has emerged as a hot topic in the field of emergency logistics. This paper focuses on the ESFs recovery problem under the constraints of scare emergency resource and recovery time. In this study, a compromise programming model is proposed as an integrated decision support tool to obtain an optimal compromise solution with regard to two objectives: minimize the consumption of recovery resources and maximize the resilience capacity through selecting different recovery strategies. Then a genetic algorithm is proposed to solve the developed mathematical model, and a numerical example is followed to illustrate the effectiveness and usefulness of proposed model. © Springer-Verlag Berlin Heidelberg 2012.
CITATION STYLE
Jiang, Y., & Zhao, L. (2012). Intelligent Decision Technologies. Smart Innovation, Systems and Technologies (Vol. 15, pp. 3–12). Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-84879256866&partnerID=tZOtx3y1
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