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An emergency logistics distribution routing model for unexpected events

Author

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  • Xiaoxia Huang

    (University of Science and Technology Beijing)

  • Liying Song

    (University of Science and Technology Beijing)

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.

Suggested Citation

  • Xiaoxia Huang & Liying Song, 2018. "An emergency logistics distribution routing model for unexpected events," Annals of Operations Research, Springer, vol. 269(1), pages 223-239, October.
    • Handle: RePEc:spr:annopr:v:269:y:2018:i:1:d:10.1007_s10479-016-2300-7
    DOI: 10.1007/s10479-016-2300-7
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    Cited by:

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    3. Esteban Ogazón & Neale R. Smith & Angel Ruiz, 2022. "Reconfiguration of Foodbank Network Logistics to Cope with a Sudden Disaster," Mathematics, MDPI, vol. 10(9), pages 1-20, April.

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