A distributionally robust optimisation with joint chance constraints approach for location-routing problem in urban search and rescue operations
针对灾后不确定需求与旅行时间，提出一个多周期选址路径优化模型，采用分布鲁棒联合机会约束方法，帮助决策者选址并调度搜救队，最大化救援率。
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.