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Multiperiod optimal emergency material allocation considering road network damage and risk under uncertain conditions

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  • Yanyan Wang

    (Tsinghua University)

  • Baiqing Sun

    (Harbin Institute of Technology)

Abstract

Material rescue is a key component of recovery and reconstruction in disaster-affected areas. Scientific and reasonable emergency material allocation (EMA) can improve rescue effects, reduce allocation risks, and minimize the losses due to a disaster. Previous EMA studies have mainly centered on complete or deterministic disaster information, while the impact of uncertain factors affecting material allocation, such as fuzzy random information and road network damage, are generally neglected. Thus, existing material allocation schemes are not fully practically applicable. This paper proposes a multiperiod optimization model for EMA under uncertain conditions with the goals of the shortest time, lowest cost, and lowest risk. A risk measurement method is incorporated into the multiperiod EMA scheme. Deterministic transformation methods of stochastic and fuzzy constrained programming, as well as an improved genetic algorithm (IGA), are applied to solve the proposed model. A computational case based on the LuDian earthquake in China is used to verify the practicability of the proposed model. The results show that the proposed risk measurement method can effectively measure multiperiod transportation risk and path repair risk in the material allocation context. Road conditions also appear to markedly impact the multiperiod allocation of emergency materials. We illustrate the relationship among risk, time, and cost plus a dimension of flexibility in various optimized multiperiod EMA scenarios. A comparative analysis of intelligent algorithms shows that the proposed IGA is the most effective approach to manage large-scale EMA optimization problems as it has higher solving efficiency, better convergence, and stronger stability.

Suggested Citation

  • Yanyan Wang & Baiqing Sun, 2022. "Multiperiod optimal emergency material allocation considering road network damage and risk under uncertain conditions," Operational Research, Springer, vol. 22(3), pages 2173-2208, July.
    • Handle: RePEc:spr:operea:v:22:y:2022:i:3:d:10.1007_s12351-021-00655-0
    DOI: 10.1007/s12351-021-00655-0
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    2. Lin Chen & Ting Dong & Jin Peng & Dan Ralescu, 2023. "Uncertainty Analysis and Optimization Modeling with Application to Supply Chain Management: A Systematic Review," Mathematics, MDPI, vol. 11(11), pages 1-45, May.

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