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设施失灵风险下不确定需求应急定位-路径鲁棒优化研究
引用本文:孙华丽,项美康.设施失灵风险下不确定需求应急定位-路径鲁棒优化研究[J].中国管理科学,2020,28(2):199-207.
作者姓名:孙华丽  项美康
作者单位:上海大学管理学院, 上海 200444
基金项目:国家自然科学基金资助项目(71974121,71603109)
摘    要:为抵御突发灾害对路网造成的破坏性和设施失灵风险,降低系统成本,并快速完成应急救援任务,本文考虑到受灾点物资需求量的不确定和风险对救援系统的影响,采用直升机进行物资运送以规避路径风险。建立了最小化应急物流系统总成本和物资到达需求点总救援时间为双目标的应急物流定位-路径鲁棒优化模型,基于相对鲁棒优化方法处理需求不确定,采用偏差鲁棒优化思想描述设施失灵风险损失,采用遗传算法进行求解。通过对三个算例进行数据仿真实验,证明了相对鲁棒优化方法在处理需求不确定和偏差鲁棒优化方法在处理设施失灵风险方面的有效性,进而为解决应急设施点的开设和救援物资的安全及时准确配送,增强应急物流系统的风险应对能力提供了有效的方法。

关 键 词:定位-路径  不确定需求  设施失灵  鲁棒优化  
收稿时间:2018-04-20
修稿时间:2018-08-10

Robust Optimization for Emergency Location-routing Problem with Uncertain Demand under Facility Failure Risk
SUN Hua-li,XIANG Mei-kang.Robust Optimization for Emergency Location-routing Problem with Uncertain Demand under Facility Failure Risk[J].Chinese Journal of Management Science,2020,28(2):199-207.
Authors:SUN Hua-li  XIANG Mei-kang
Institution:Management School, Shanghai University, Shanghai 200444, China
Abstract:The frequent occurrence of earthquakes has brought great threats to people and seriously affected economic development and social stability. To reduce the loss caused by disasters and response quickly, it is urgent to realize scientific optimization of emergency facilities location and relief material distribution with the constraints of time, space and resource. However, inadequate information and the destructiveness of emergency disasters often lead to the uncertain emergency demand. And the disasters often damage the roads and make facilities failure, which bring great risks to the distribution of the emergency relief. Therefore, it is necessary to consider the relief uncertainty and the risk of facility failure after emergency. In this paper, demand uncertainty is described by a specified interval. A robust optimization model is proposed to combine the emergency location and the routing problem using helicopters, whose objective is to minimize total transportation time and the total system costs. The risk of facility failure is solved by the robust deviation optimization and the model is solved by genetic algorithm. Finally, numerical examples from Wang's LRP problem verified the validity of the model and algorithm Comparisons of three cases indicate that the total system cost increases as the growth of the budget of uncertainty and the data variability. The results further show that the relative robust optimization method can deal with the uncertain demand effectively, and the robust deviation optimization method can avoid the risk of emergency logistics system. It provides an effective method to help post-disaster managers to determine the emergency location and delivery the relief safely, timely.
Keywords:location-routing  uncertain demand  facility failure  robust optimization  
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