A distributionally robust optimisation with joint chance constraints approach for location-routing problem in urban search and rescue operations

IF 4.1 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Kamran Sarmadi , Mehdi Amiri-Aref
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引用次数: 0

Abstract

This paper examines a multi-period location-routing problem with uncertain demand and travel times in the context of disaster management. We propose an optimisation model that integrates strategic location decisions with multi-period routing decisions to navigate search-and-rescue teams in the aftermath of a disaster within an uncertain environment. To model this problem, we apply a distributionally robust optimisation approach with joint chance constraints. We enhance computational tractability by reformulating the problem using Bonferroni’s inequality and approximating the chance constraints. The proposed methodology is evaluated in a hypothetical case study of Santa Cruz County, California, USA, a region highly susceptible to earthquakes. We tested multiple instances of this case study to demonstrate the effectiveness of the proposed method compared to the sample average approximation approach. Numerical experiments reveal that the methodology developed in this paper aids decision-makers in strategically locating facilities to deploy search-and-rescue teams and efficiently directing them towards affected sites, achieving a maximal rescue rate.
城市搜救中位置路径问题的联合机会约束分布鲁棒优化方法
本文研究了灾害管理背景下具有不确定需求和出行时间的多周期定位路径问题。我们提出了一个优化模型,该模型集成了战略位置决策和多周期路径决策,以便在不确定的环境中为灾难后的搜救队导航。为了对这个问题建模,我们应用了一个具有联合机会约束的分布鲁棒优化方法。我们通过使用Bonferroni不等式和近似机会约束来重新表述问题,从而提高了计算的可追溯性。建议的方法在美国加利福尼亚州圣克鲁斯县的一个假设案例研究中进行了评估,这是一个高度易受地震影响的地区。我们测试了本案例研究的多个实例,以证明与样本平均近似方法相比,所提出方法的有效性。数值实验表明,本文开发的方法有助于决策者战略性地定位设施,部署搜救队伍,并有效地将他们引导到受影响的地点,实现最大的救援率。
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来源期刊
Computers & Operations Research
Computers & Operations Research 工程技术-工程:工业
CiteScore
8.60
自引率
8.70%
发文量
292
审稿时长
8.5 months
期刊介绍: Operations research and computers meet in a large number of scientific fields, many of which are of vital current concern to our troubled society. These include, among others, ecology, transportation, safety, reliability, urban planning, economics, inventory control, investment strategy and logistics (including reverse logistics). Computers & Operations Research provides an international forum for the application of computers and operations research techniques to problems in these and related fields.
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