A robust model for emergency supplies prepositioning and transportation considering road disruptions

IF 3.7 4区 管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Operations Research Perspectives Pub Date : 2023-01-01 DOI:10.1016/j.orp.2023.100266
Wuyang Yu
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Abstract

Proper prepositioning of emergency supplies can dramatically improve the efficiency of emergency response work. However, the uncertainties of emergency demands and road conditions bring difficulties to the prepositioning of emergency supplies. This paper proposes a two-stage robust model to locate emergency supply points and preposition the corresponding storage amount of emergency supplies, in which we presented two budget sets to describe the uncertainties of demands and road conditions, respectively. The innovative use of variables in the model to limit road capacities addresses the representation of different road interruption scenarios. We proposed an algorithm based on Benders decomposition by transforming the second-stage model into a binary linear programming model. Computational experiments based on the Sioux Falls network demonstrate the validity of the model and algorithm. We conducted sensitivity analyses for some important parameters in the model, such as two uncertainty control parameters, unit transportation cost, budget for the construction of emergency supply points, etc. We find that the uncertainty of road disruptions has a greater impact on the model than the uncertainty of demands. In addition, when the control parameter of the road disruptions exceeds a certain threshold, its influence on the model remains essentially constant.

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考虑道路中断的应急物资预先定位和运输的稳健模型
适当地预先部署应急物资可以极大地提高应急工作的效率。然而,应急需求和道路状况的不确定性给应急物资的预先部署带来了困难。本文提出了一个两阶段鲁棒模型来定位应急供应点并预先确定相应的应急物资储存量,其中我们分别提出了两个预算集来描述需求和道路状况的不确定性。模型中创新性地使用变量来限制道路通行能力,解决了不同道路中断场景的表示问题。我们提出了一种基于Benders分解的算法,将第二阶段模型转换为二元线性规划模型。基于Sioux-Falls网络的计算实验验证了模型和算法的有效性。我们对模型中的一些重要参数进行了敏感性分析,如两个不确定性控制参数、单位运输成本、应急供应点建设预算等。我们发现,道路中断的不确定性比需求的不确定性对模型的影响更大。此外,当道路中断的控制参数超过一定阈值时,其对模型的影响基本保持不变。
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来源期刊
Operations Research Perspectives
Operations Research Perspectives Mathematics-Statistics and Probability
CiteScore
6.40
自引率
0.00%
发文量
36
审稿时长
27 days
期刊最新文献
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