Two-stage robust facility location problem with drones
Two-stage robust facility location problem with drones
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DOI：
10.1016/j.trc.2022.103563
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发表时间：
2022-04
期刊：
影响因子：
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通讯作者：
Te Zhu;S. Boyles;A. Unnikrishnan
中科院分区：
文献类型：
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作者：
Te Zhu;S. Boyles;A. Unnikrishnan
在过去的几年里，无人机在物流、农业、军事和电信等各个行业的应用越来越多。本文研究了一种短期灾后无人机（UAV）人道主义救援应用，需要将急救产品运送到客户需求点。所提出的问题，两阶段的鲁棒设施选址问题与无人机（两阶段RFLPD），采用需求场景的需求不确定性。该问题的目标是在所有可能的需求结果的最坏情况下，找到一个具有最小两阶段总成本的位置分配计划。提出了三种不同的模型的问题，其中两个包含一个现实的无人机电力消耗模型，而最后一个具有更大的操作灵活性。采用列约束生成法和Benders分解法对两个模型进行求解，并对带无人机的确定性设施选址问题（FLPD）模型和三个提出的模型进行了比较。数值分析结果表明，所提出的模型具有显着更少的平均成本在模拟运行相比，确定性FLPD。
The past few years have witnessed the increasing adoption of drones in various industries such as logistics, agriculture, military, and telecommunications. This paper considers a short-term post-disaster unmanned aerial vehicle (UAV) humanitarian relief application where first-aid products need to be delivered to the customer demand points. The presented problem, two-stage robust facility location problem with drones (two-stage RFLPD), incorporates the demand uncertainty using demand scenarios. This problem aims to find a location–allocation-assignment plan that has minimal two-stage total cost in the worst-case scenario of all the possible demand outcomes. Three different models of the problem are proposed, two of which incorporate a realistic UAV electricity consumption model while the last one has greater operational flexibility. The column-and-constraint generation method and Benders decomposition are used to solve the two models, and a thorough comparison among the deterministic facility location problem with drones (FLPD) models and three proposed models are also presented. Numerical analysis results show that the proposed model has significantly less average cost in the simulation runs compared to the deterministic FLPD.