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A robust optimization approach to postdisaster relief logistics planning under uncertainties

机译:不确定性下灾后物流规划的鲁棒优化方法

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A stochastic model with bi-objective for post disaster relief logistics is proposed to decide the strategic planning on the mobilization levels of relief supplies, the initial deployment of vehicles and the transportation plans within the disaster region in a uncertain disaster environment. The robust optimization approach is introduced to cope with uncertainties and the robust counterpart of the proposed stochastic model is deduced. A lexicographic approach is utilized to convert the bi-objective robust model into two sequential single objective robust models. Numerical experiments show that the model can help post-disaster managers to determine the initial deployment of emergency resources, and the numerical results can express the tradeoff between optimization and robustness.
机译:提出了灾后后勤物流的双目标随机模型,用于在不确定的灾后环境中,确定灾区救灾物资的动员水平,车辆的初次部署和运输计划的战略规划。引入了鲁棒优化方法来应对不确定性,并推导了所提出的随机模型的鲁棒对应物。利用词典方法将双目标鲁棒模型转换为两个连续的单目标鲁棒模型。数值实验表明,该模型可以帮助灾后管理人员确定应急资源的初始部署,数值结果可以表达优化与鲁棒性之间的权衡。

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