A scenario-based hybrid robust and stochastic approach for joint planning of relief logistics and casualty distribution considering secondary disasters
A scenario-based hybrid robust and stochastic approach for joint planning of relief logistics and casualty distribution considering secondary disasters
复制标题
考虑次生灾害的基于场景的混合鲁棒随机方法用于联合规划救援物流和伤亡分配
DOI：
10.1016/j.tre.2020.102029
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发表时间：
2020-09-01
影响因子：
10.6
通讯作者：
Yu, Guodong
中科院分区：
文献类型：
--
作者：
Li, Yuchen;Zhang, Jianghua;Yu, Guodong
提出了一种基于情景的三阶段混合稳健随机模型，在不确定的原生和次生灾害组合情景下，对响应网络进行优化设计，并有效地分配人员伤亡。根据组合灾害的随机严重程度，分别针对疏散人员规模和运输时间的模糊不确定性推导了稳健对应关系。为了解决这一问题，提出了一种基于增广拉格朗日松弛的定制渐进套期保值算法。我们基于情景对问题进行分解，迭代求解决策变量与阶段无关的自适应惩罚的子问题。一个说明性例子的结果表明，纳入次生灾害情景有助于提高救济覆盖面。与一些基准测试结果相比，该算法具有较强的竞争力。
This paper proposes a scenario-based three-stage hybrid robust and stochastic model that optimally designs the response network and distributes casualties effectively under uncertain combinational scenarios of primary and secondary disasters. Following the stochastic severity of combinational disasters, the robust counterparts are derived against the ambiguous uncertainty of evacuee scales and transportation time, respectively. A customized progressive hedging algorithm based on the augmented Lagrangian relaxation is developed to solve the problem. We decompose the problem based on the scenario and iteratively solve the adaptively penalized subproblems with decision variables independent of stages. The results of an illustrative example show that incorporating secondary disaster scenarios can contribute to improving relief coverage. The proposed algorithm is competitive with some benchmarks.