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Multi-objective stochastic programming model for relief allocation based on disaster scenario information updates
ZHAN Sha-lei, LIU Nan
Systems Engineering - Theory & Practice ›› 2013, Vol. 33 ›› Issue (1) : 159-166.
PDF(1294 KB)
PDF(1294 KB)
Multi-objective stochastic programming model for relief allocation based on disaster scenario information updates
This paper addressed a multi-supplier multi-affected area multi-relief and multi-vehicle emergency vehicles location, path selection and relief allocation problem. Considering the inherent trade-off between disaster forecast accuracy and logistics cost efficiency, a multi-objective stochastic programming model was proposed. The features were: the demand and availability of relief-allocation path were stochastic, and there were coverage limits for relief suppliers to cover affected areas. The multi-objective programming model was transformed into a single-objective programming model by the use of a weighted Bayes risk; and the proposed model was transformed into an optimal stopping problem by designing a decision rule. The model was solved by using Xpress. Numerical results indicate the velocity and accuracy of the model and software, and demonstrate the superiority of two-stage stochastic programming and disaster scenario information updates respectively.
emergency logistics / multi-objective stochastic programming / information updates / Bayes risk / optimal stopping problem {{custom_keyword}} /
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