车机协同下多级应急网络物资配送优化研究数据集

针对情景演变下的物资动态需求问题，面向航空、铁路、公路及无人机等多种运输方式建立应急物资动态调度模型，实现群智感知获取实时多维数据基础上的多演化阶段、多运输方式、多物资品类的物流优化调度。选取了成都市青白江区、新都区、成华区等区域为节点依据，并利用实际数据和仿真结合的方法进行参数设置。配送网络包括3个应急物资仓、4个城市配送中心和40个临时配送站。各临时配送站有对应的经纬度、需求量信息。配送站的经纬度通过百度地图获取，需求量基于实际需求设置，数据量12KB。To address the dynamic material demand problem under scenario evolution, a dynamic emergency supplies dispatching model is developed for multiple transport modes including aviation, railway, highway, and unmanned aerial vehicles (UAVs). This model enables optimal logistics scheduling across multiple evolutionary stages, transport modes, and material categories based on real-time multi-dimensional data collected through crowd sensing. Regions including Qingbaijiang District, Xindu District, and Chenghua District of Chengdu City are selected as the basis for node deployment, and parameter settings are conducted via a method combining actual field data and simulation experiments. The distribution network consists of 3 emergency material warehouses, 4 urban distribution centers and 40 temporary distribution stations. Each temporary distribution station has corresponding longitude and latitude coordinates and demand information. The coordinates of the distribution stations are obtained via Baidu Maps, while the demand values are set based on actual demands, with a total data volume of 12 KB.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于车机协同下的应急物资配送优化问题，通过建立多运输方式动态调度模型，利用群智感知实时数据支持多阶段、多品类物流调度。它以成都市部分区域为节点，包含应急物资仓、配送中心和临时配送站等网络结构，数据基于实际需求设置，涵盖经纬度与需求量信息。