Abstract
In the case of large-scale natural disaster, it is very important to determine emergency materials scheduling quickly and efficiently from multiple emergency logistics centers as supply points supplying to multiple disasters affected points. In order to improve the efficiency of supplying organization and reduce casualties and economic losses, a mathematical model is first constructed in this paper to minimize the total emergency cost including emergency response system cost and the loss caused by untimely rescue. Then, a memetic algorithm (MA) using natural coding is proposed to solve the problem, and the experimental results show that the performance of this algorithm is much better than that of genetic algorithm (GA). At the same time, the proposed model and algorithm provide robust support for decision makers when quick responses are necessary for disaster relief activities.
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Acknowledgements
This work is partially supported by the Outstanding Young Scholar Program of National Natural Science Foundation of China (NSFC) under Grant 61522311, the overseas, Hong Kong & Macao Scholars Collaborated Research Program of NSFC under Grant 61528205, and the Key Program of Fundamental Research Project of Natural Science of Shanxi Province, China under Grant 2017JZ017.
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Qin, Y., Liu, J. (2017). Emergency Materials Scheduling in Disaster Relief Based on a Memetic Algorithm. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10637. Springer, Cham. https://doi.org/10.1007/978-3-319-70093-9_29
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DOI: https://doi.org/10.1007/978-3-319-70093-9_29
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