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Aug 12, 2020
A Rescue Vehicle Routing Optimization Model Considering Timely Replenishment
Authors: Xiran Zhang [email protected], Xinchen Ran [email protected], Shaokuan Chen, Ph.D. [email protected], and Shiyao Peng [email protected]Author Affiliations
Publication: CICTP 2020
ABSTRACT
This paper aims to optimize the emergency rescue efficiency with a vehicle routing model. In order to make the problem more realistic, the model takes into account a replenishment strategy which can be chosen by the rescue vehicles flexibly when their remaining supplies are insufficient. In particular, the strategy is subdivided into two replenishment methods according to the different routings, and the same demand point is allowed to be covered by multiple vehicles during the rescue. The model attempts to minimize the working hours of the vehicle with the longest rescue time. Moreover, an adapted bat algorithm with two repair factors is devised to solve the model. The case study shows that applying a flexible replenishment strategy results in less rescue time, and the working hours of each vehicle are more balanced. Therefore, the model can improve rescue efficiency and provide reference for vehicle dispatching after disasters.
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© 2020 American Society of Civil Engineers.
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Published online: Aug 12, 2020
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1MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong Univ., No. 3 Shangyuancun Haidian District, Beijing 100044, PR China. Email: [email protected]
2MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong Univ., No. 3 Shangyuancun Haidian District, Beijing 100044, PR China. Email: [email protected]
3MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong Univ., No. 3 Shangyuancun Haidian District, Beijing 100044, PR China. Email: [email protected]
4MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong Univ., No. 3 Shangyuancun Haidian District, Beijing 100044, PR China. Email: [email protected]
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