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Mathematical Problems in Engineering
Volume 2016 (2016), Article ID 5030619, 9 pages
Research Article

Optimization on Emergency Resources Transportation Network Based on Bayes Risk Function: A Case Study

1School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou 730070, China
2School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China

Received 27 January 2016; Revised 14 May 2016; Accepted 5 June 2016

Academic Editor: Rita Gamberini

Copyright © 2016 Changfeng Zhu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In order to coordinate the complex relationship between supplies distribution and path selection, some influential factors must be taken into account such as the insufficient remaining capacity of the road and uncertainty of travel time during supplies distribution and transportation. After the structure of emergency logistics network is analyzed, the travel time Bayes risk function of path and the total loss Bayes risk function of the disaster area are proposed. With the emergency supplies total transportation unit loss as the goal, an emergency logistics network optimization model under crowded conditions is established by the Bayes decision theory and solved by the improved ant colony algorithm. Then, a case of the model is validated to prove that the emergency logistics network optimization model is effective in congested conditions.