考虑需求紧迫度的应急车辆路径优化方法

Route optimization method for emergency vehicles considering demand urgency

摘要:

为提高应急管理水平,量化各受灾点物资需求紧迫度,提出考虑紧迫度的车辆最优路径规划方法。采用K-means聚类算法确定应急物资配送中心的选择以及受灾点的划分,以应急救援过程中的总时间最短、救援所花费的总费用最小以及受灾点紧迫度排序指数最大为目标,构建多目标的应急车辆路径优化模型,并设计改进的布谷鸟-蚁群组合算法进行求解。以汶川地震为背景构造算例,验证模型的有效性,结果表明:与不考虑需求紧迫度的车辆路径方案相比,考虑需求紧迫度的路径优化方案在所需运输总时间上升1.92%、救援过程总费用增加3.43%的前提下,紧迫度排序指数提高了11.2%。考虑需求紧迫度的车辆路径优化模型在保障突发灾害救援效率的同时,兼顾了不同受灾点的物资需求程度,提高了应急物资运送的公平性。

Abstract:

For the improvement of emergency management, the degree of material demand for different disaster-stricken sites was quantified, and an optimal route planning method for vehicles was proposed considering the urgency of demand. The K-means clustering algorithm was utilized to determine the selection of emergency material distribution centers and the division of disaster-affected points. With the shortest total time in the emergency rescue process, the minimum total cost of the rescue, and the maximum urgency ranking index of the disaster-affected points as the goal, a multi-objective emergency vehicle routing optimization model was established, and an improved cuckoo-ant colony hybrid algorithm was designed to solve it. Taking the Wenchuan earthquake as the background, the effectiveness of the proposed model was verified. Results show that compared with the vehicle routing scheme without considering demand urgency, the routing optimization scheme considering demand urgency increased the urgency ranking index by 11.2% on the premise that the total transportation time and the total cost of rescue process increased by 1.92% and 3.43%. The vehicle routing optimization model considering the urgency of demand not only ensures the rescue efficiency of sudden disasters, but also considers the material demand degree of different disasters-affected points, and improves the fairness of emergency material transportation.