(1.长沙理工大学 智能道路与车路协同湖南省重点实验室 ，湖南 长沙 410114;2.湖南省交通科学研究院 智慧交通事业部，湖南 长沙 410029;3.同济大学 道路与交通工程教育部重点实验室 ，上海市 201804)
龙科军，男，博士，教授.E-mail：Longkejun@csust.edu.cn
张仲根，男，博士研究生.E-mail：zhangzhonggen@tongji.edu.cn
U491
国家自然科学基金资助项目（编号：52172313，52402371）；湖南省自然科学基金资助项目（编号：2023JJ30033，2024JJ6037）；长沙市科技重大专项（编号：kh2301004）；长沙理工大学智能道路与车路协同湖南省重点实验室开放基金资助项目（编号：kfj230802）
ZHANG Zhonggen
Hunan Key Laboratory of Smart Roadway and Cooperative Vehicle-Infrastructure Systems , Changsha University of Science & Technology , Changsha ， Hunan 410114 , China ;Experimental Teaching Center of Transportation Engineering , Tongji University , Shanghai 201804 , China(1.Hunan Key Laboratory of Smart Roadway and Cooperative Vehicle-Infrastructure Systems , Changsha University of Science & Technology , Changsha ， Hunan 410114 , China ; 2.Smart Transportation Division , Hunan Academy of Transportation Sciences , Changsha ， Hunan 410029 , China ; 3.Experimental Teaching Center of Transportation Engineering , Tongji University , Shanghai 201804 , China )
突发事件下的应急车辆调度，既要优先考虑需求紧迫度高的关键节点，又要避免其他节点配送延时过大产生次生影响。基于此，该文建立了考虑需求紧迫度与配送延时公平的应急车辆调度模型。首先，采用熵权 -TOPSIS 法计算节点需求紧迫度，并引入配送延时均衡指标避免节点之间的配送延时差异过大；其次，以配送的总时间、总成本和配送延时均衡度为多目标函数，配送中心库存量、路径连续性等为约束条件，建立优化模型；最后，通过 K-Means 算法和CW节约算法划分子路网，结合可变邻域局部搜索算法改进蚁群算法。结果表明：相比于基本模型，所提模型下，需求紧迫度高的节点的平均配送延时和最大配送延时分别降低 25.26%、22.98%，配送延时方差增加 34.30%；相比于仅考虑需求紧迫度的模型，所提模型下，需求紧迫度高节点的平均配送延时、最大配送延时和配送延时方差分别降低10.79%、20.26%和40.57%。这表明所提模型能更好地兼顾关键节点的优先和普通节点的公平。
In emergency vehicle dispatching after unexpected events，it is crucial to prioritize critical nodes with high demand urgency while minimizing excessive delivery delays at other nodes to prevent secondary impacts.On this basis，this study developed an emergency vehicle dispatching model that considered demand urgency and delivery delay fairness.Firstly，the entropy weight-TOPSIS method was used to calculate the demand urgency for each node，and a delivery delay balance index was introduced to minimize disparities in delivery delays between nodes.Secondly，a multi-objective optimization model was established with total delivery time，overall cost，and delivery delay balance as objectives，while considering constraints such as inventory levels at distribution centers and route continuity.Finally，the K-Means algorithm and the Clarke-Wright （CW） saving algorithm were employed to partition the sub-networks，and an improved ant colony algorithm incorporating a variable neighborhood local search was applied.The results indicate that compared with the basic model，the proposed model reduces the average and maximum delivery delays at nodes with high demand urgency by 25.26% and 22.98%，respectively，while increasing the delivery delay variance by 34.30%.Compared with a model considering only demand urgency，the proposed model decreases the average delivery delay，maximum delivery delay，and delivery delay variance at nodes with high demand urgency by 10.79%，20.26%，and 40.57%，respectively.These findings demonstrate that the proposed model effectively balances priority for critical nodes with fairness for standard nodes.
龙科军,刘嘉,高志波,等.考虑配送紧迫度与公平的应急车辆调度模型[J].中外公路,2024,44(6):251-258.
LONG Kejun, LIU Jia, GAO Zhibo, et al. Emergency Vehicle Dispatching Model Considering Demand Urgency and Delivery Fairness[J]. Journal of China & Foreign Highway,2024,44(6):251-258.
