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Model and algorithm of routes planning for emergency relief distribution in disaster management with disaster information update

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  • Jianming Zhu

    (University of Chinese Academy of Sciences)

  • Shuyue Liu

    (University of Chinese Academy of Sciences)

  • Smita Ghosh

    (University of Texas at Dallas)

Abstract

Emergency relief distribution plays a vital role during disaster responding. This paper studies routes selection and transportation time moment selection for emergency relief distribution along with disaster information updating. This paper derives a new definition for route reliability, which is a combination of multiple routes according to three factors: reliability of each edge, the number of dissimilar detour paths, and dissimilarity of multiple routes. Transportation time moment is determined according to disaster information updating accuracy rate. A multi-objective mathematical programming is formulated for route planning problem. The objective function consists route reliability and information accuracy rate. Then we present an ant colony optimization algorithm to solve this problem. Disaster information update process is clarified, as well as propose a new way to evaluate multiple routes reliability and applying an improved ant colony optimization algorithm. Finally, an earthquake around Ludian in Yunnan Provence is considered as a disaster scenario to analyze our model and algorithm, include the optimal solution, parameters’ impact on objective function, and performance of our algorithms.

Suggested Citation

  • Jianming Zhu & Shuyue Liu & Smita Ghosh, 2019. "Model and algorithm of routes planning for emergency relief distribution in disaster management with disaster information update," Journal of Combinatorial Optimization, Springer, vol. 38(1), pages 208-223, July.
    • Handle: RePEc:spr:jcomop:v:38:y:2019:i:1:d:10.1007_s10878-018-00377-8
    DOI: 10.1007/s10878-018-00377-8
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    References listed on IDEAS

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    1. Pushak, Yasha & Hare, Warren & Lucet, Yves, 2016. "Multiple-path selection for new highway alignments using discrete algorithms," European Journal of Operational Research, Elsevier, vol. 248(2), pages 415-427.
    2. Raka Jovanovic & Abdelkader Bousselham & Stefan Voß, 2018. "Partitioning of supply/demand graphs with capacity limitations: an ant colony approach," Journal of Combinatorial Optimization, Springer, vol. 35(1), pages 224-249, January.
    3. Liang Song & Hejiao Huang & Hongwei Du, 2016. "Approximation schemes for Euclidean vehicle routing problems with time windows," Journal of Combinatorial Optimization, Springer, vol. 32(4), pages 1217-1231, November.
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    Cited by:

    1. Ling Gai & Zhiyue Peng & Jiming Zhang & Jiafu Zhang, 2021. "Emergency medical center location problem with people evacuation solved by extended TODIM and objective programming," Journal of Combinatorial Optimization, Springer, vol. 42(4), pages 1004-1029, November.
    2. Ling Gai & Zhiyue Peng & Jiming Zhang & Jiafu Zhang, 0. "Emergency medical center location problem with people evacuation solved by extended TODIM and objective programming," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-26.
    3. Peng Wu & Ling Xu & Ada Che & Feng Chu, 2022. "A bi-objective decision model and method for the integrated optimization of bus line planning and lane reservation," Journal of Combinatorial Optimization, Springer, vol. 43(5), pages 1298-1327, July.

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