In this paper, a latency location-routing problem with stochastic travel times is investigated. The problem is cast as a two-stage stochastic program. The ex-ante decision comprises the location of the depots. The ex-post decision regards the routing, which adapts to the observed travel times. A risk-averse decision-maker is assumed, which is conveyed by adopting the latency CVaRα as the objective function. The problem is formulated mathematically. An efficient multi-start variable neighborhood search algorithm is proposed for tackling the problem when uncertainty is captured by a finite set of scenarios. This procedure is then embedded into a sampling mechanism so that realistic instances of the problem can be tackled, namely when the travel times are represented by random vectors with an infinite support. An extensive computational analysis is conducted to assess the methodological developments proposed and the relevance of capturing uncertainty in the problem. Additional insights include the impact of the risk level in the solutions.

中文翻译：

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具有随机旅行时间的规避风险的延迟位置路由问题


在本文中，研究了随机旅行时间的延迟位置路由问题。该问题被转换为两阶段随机程序。事前决定包括车辆段的位置。事后决策涉及路线，该路线会根据观察到的行驶时间进行调整。假设一个规避风险的决策者，通过采用延迟 CVaRα 作为目标函数来传达这一点。该问题是用数学方式表述的。该文提出一种高效的多起点变量邻域搜索算法，以解决当不确定性被一组有限场景捕获时的问题。然后将此过程嵌入到采样机制中，以便可以处理问题的实际实例，即当旅行时间由具有无限支持的随机向量表示时。进行了广泛的计算分析，以评估所提出的方法发展以及捕获问题中不确定性的相关性。其他见解包括解决方案中风险级别的影响。