An emergency logistics distribution routing model for unexpected events

Xiaoxia Huang () and Liying Song
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Xiaoxia Huang: University of Science and Technology Beijing
Liying Song: University of Science and Technology Beijing

Annals of Operations Research, 2018, vol. 269, issue 1, No 13, 223-239

Abstract: Abstract Though there are many specialities of logistics distribution in unexpected events, the greatest uniqueness of the problem should be the feature that no historical data about some parameters are available. The paper defines the emergency logistics as the one of which the parameters have no historical data due to the occurrence of the unexpected events, and discusses an emergency logistics distribution routing problem in which demands of the affected areas and road travel times lack historical data and are given by experts’ estimations. Uncertain variables are used to describe the experts’ estimates of the parameters and the use of them is justified. An emergency logistics distribution routing model is developed based on uncertainty theory. To solve the problem, the equivalent model is provided and a cellular genetic algorithm is designed. In addition, an example is presented to illustrate the application of the proposed model and the effectiveness of the proposed algorithm.

Keywords: Vehicle routing problem; Emergency logistics; Uncertain programming; Uncertainty theory; Genetic algorithm (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10479-016-2300-7

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