Purpose

This study aims to minimize the expected arrival time of relief vehicles to the affected areas, considering the destruction of potential routes and disruptions due to disasters. In relief operations, required relief items in each affected area and disrupted routes are considered as uncertain parameters. Additionally, for a more realistic consideration of the situations, it is assumed that the demand of each affected area could be met by multiple vehicles and distribution centers (DCs) and vehicles have limited capacity.

Design/methodology/approach

The current study developed a two-stage stochastic programming model for the distribution of relief items from DCs to the affected areas. Locating the DCs was the first-stage decisions in the introduced model. The second-stage decisions consisted of routing and scheduling of the vehicles to reach the affected areas.

Findings

In this paper, 7th district of Tehran was selected as a case study to assess the applicability of the model, and related results and different sensitivity analyses were presented as well. By carrying out a simultaneous sensitivity analysis on the capacity of vehicles and the maximum number of DCs that can be opened, optimal values for these parameters were determined, that would help making optimal decisions upon the occurrence of a disaster to decrease total relief time and to maximize the exploitation of available facilities.

Originality/value

The contributions of this paper are as below: presenting an integrated model for the distribution of relief items among affected areas in the response phase of a disaster, using a two-stage stochastic programming approach to cope with route disruptions and uncertain demands for relief items, determining location of the DCs and routing and scheduling of vehicles to relief operations and considering a heterogeneous fleet of capacitated relief vehicles and DCs with limited capacity and fulfilling the demand of each affected area by more than one vehicle to represent more realistic situations.

中文翻译：

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中断和不确定性下救灾中交通规划的随机优化

目的

考虑到潜在路线的破坏和灾害造成的中断，本研究旨在最大限度地减少救援车辆到达受灾地区的预期时间。在救援行动中，每个受影响地区和中断路线所需的救援物品被视为不确定参数。此外，为了更现实地考虑情况，假设每个受影响区域的需求可以通过多个车辆和配送中心 (DC) 来满足，并且车辆的容量有限。

设计/方法/方法

目前的研究开发了一个两阶段随机规划模型，用于将救济物品从 DC 分配到受灾地区。定位 DC 是引入模型中的第一阶段决策。第二阶段的决策包括车辆的路线选择和调度，以到达受影响的地区。

发现

本文选择德黑兰第七区作为案例研究，评估模型的适用性，并给出相关结果和不同的敏感性分析。通过对车辆的容量和可打开的最大 DC 数量进行同步敏感性分析，确定这些参数的最佳值，这将有助于在灾难发生时做出最佳决策，以减少总救援时间并最大限度地利用现有设施。

原创性/价值

本文的贡献如下： 提出了灾害响应阶段救援物资在受灾地区分配的综合模型，采用两阶段随机规划方法来应对路线中断和不确定的救援物资需求，确定 DC 的位置，以及为救援行动安排车辆的路线和调度，并考虑由有能力的救援车辆和容量有限的 DC 组成的异构车队，并通过不止一辆车辆满足每个受灾地区的需求，以代表更现实的情况。