American Journal of Electrical and Electronic Engineering. 2019, 7(3), 83-90
DOI: 10.12691/AJEEE-7-3-5
Original Research

An Optimal Distribution Model of Emergency Materials Based on Disaster Weather

Guanghui Wang1,

1Chinese Academy of Meteorological Sciences, Beijing 100081, China

Pub. Date: September 05, 2019

Cite this paper

Guanghui Wang. An Optimal Distribution Model of Emergency Materials Based on Disaster Weather. American Journal of Electrical and Electronic Engineering. 2019; 7(3):83-90. doi: 10.12691/AJEEE-7-3-5

Abstract

Effective support of emergency materials is a necessary prerequisite for post-disaster emergency rescue. The transportation and distribution of post-disaster emergency materials includes two stages: from storage warehouses and material distribution centers outside the disaster area to emergency distribution centers outside the disaster area, and from emergency distribution centers to rescue points in the disaster area. Emergency material support has the characteristics of urgent demand and relative shortage of materials. Especially, the transportation of materials from supply points outside the disaster-stricken areas to emergency material distribution centers, along the way, affected by the actual traffic capacity and meteorological conditions, will have a significant impact on the efficient distribution of emergency materials. This paper deals with the optimization of transportation allocation from emergency material supply points to emergency material distribution centers in the periphery of disaster areas. Based on the factors affecting transportation efficiency such as road resistance parameters, attenuation coefficient, and disaster intensity, an optimal allocation model of emergency materials is established, which minimizes the sum of transportation cost, construction cost of distribution center, and penalty cost of transportation time. The validity and feasibility of the model are analyzed and studied by an example. The experimental results show that the attenuation coefficient of the transportation line and the disaster intensity of the road section have important influence on the emergency material allocation scheme. The emergency material allocation scheme formulated by the optimization model is scientific and reasonable.

Keywords

emergency supplies distribution, distribution centre, attenuation coefficient, road disaster intensity, optimal location

Copyright

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References

[1]  Haghani A, Oh S C. Formulation and solution of a multi-commodity, multimodel network flow model for disaster relief operations, Transportation Research A, 30(3), 231-250, 1996.
 
[2]  Oh S C, Haghani A. Testing and evaluation of a multi-commodity multimodel network flow model for disaster relief management, Journal of Advanced Transportation, 31(3), 249-282, 1997.
 
[3]  Feng Chun, Xiang Yang, et al, Multi-objective Optimization Model of the Emergency Logistics Distribution with Multicycle and Multi-item, Chinese Journal of Management Science, 25(4), 124-132, Apr. 2017.
 
[4]  Lou Zhen-kai, Bi-level Programming Model and Algorithm of Location-routing Problem in Emergency Logistics, Chinese Journal of Management Science, 25(11), 151-157, Nov. 2017.
 
[5]  Qu Chong-chong, Wang Jin, et al, Dynamic Emergency Materials Distribution with Timeliness and Fairness Objective for Post-Earthquake Emergency Rescue, Chinese Journal of Management Science, 26(6), 178-187, Jun. 2018.
 
[6]  Liu Chang-shi, Peng Yi, Kou Gang, Research on Fuzzy Location-routing Problem in Post-earthquake Delivery of Relief Materials, Chinese Journal of Management Science, 24(5), 111-118, May 2018.
 
[7]  Sheu J B. An emergency logistics distribution approach for quick response to urgent relief demand in disasters, Transportation Research Part E Logistics & Transportation review, 43(6), 687-709, 2007.
 
[8]  Lam W H K, Shao H, Sumalee A. Modeling impacts of adverse weather conditions on a road network with uncertainties in demand and supply, Transportation Research Part B, 42(10), 890-910, 2008.
 
[9]  Zhu Li, Sang Dan-qiu, Emergency Transportation Path Selection Based on Meteorological Information, China Safety Science Journal, 22(7), 171-176, Jul. 2012.