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Copyright of Journal of Earth Sciences & Environment is the property of Journal of Earth Sciences & Environment and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Copyright of Journal of Bohai University (Philosophy & Social Science Edition) / Bohai Daxue Xuebao (Zhexue Shehuikexue Ban) is the property of Bohai Daxue and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Northeastern University (Natural Science) is the property of Dongbei Daxue Xuebao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The emergence resources are limited and the demands are uncertain in the critical period of the disaster. In order to improve the efficiency of the emergence logistics, the allocation of the emergence resources and the vehicle routing should be determined simultaneously. Based on the assumption of the stochastic demands were normal distributions, it developed the optimal model of the emergence vehicle routing considering the stochastic demand, which objective function was to minimize the transportation costs and the costs caused by the supplies more or less than the actual demands, under the conditions of the time windows and load capacity. According to the characteristic of the model, this paper proposed the genetic algorithm to solve the model. The application shows that the method operates quickly and the results are rational, which can provide scientific basis for decision-making. [ABSTRACT FROM AUTHOR]