Endogenous stochastic optimisation for relief distribution assisted with unmanned aerial vehicles

编号 030025404

推送时间 20200831

研究领域 森林经理 

年份 2020 

类型 期刊 

语种 英语

标题 Endogenous stochastic optimisation for relief distribution assisted with unmanned aerial vehicles

来源期刊 OR SPECTRUM

期 第254期

发表时间 20200818

关键词 Relief optimisation;  Endogenous uncertainty;  Damage assessment;  Unmanned aerial vehicles; 

摘要 Unmanned aerial vehicles (UAVs) have been increasingly viewed as useful tools to assist humanitarian response in recent years. While organisations already employ UAVs for damage assessment during relief delivery, there is a lack of research into formalising a problem that considers both aspects simultaneously. This paper presents a novel endogenous stochastic vehicle routing problem that coordinates UAV and relief vehicle deployments to minimise overall mission cost. The algorithm considers stochastic damage levels in a transport network, with UAVs surveying the network to determine the actual network damages. Ground vehicles are simultaneously routed based on the information gathered by the UAVs. A case study based on the Haiti road network is solved using a greedy solution approach and an adapted genetic algorithm. Both methods provide a significant improvement in vehicle travel time compared to a deterministic approach and a non-assisted relief delivery operation, demonstrating the benefits of UAV-assisted response.

服务人员 付贺龙

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