无人机应急物资配送投放点选址分配（IHS Allocation）算法数据集

针对应急物资动态调度问题，以救助时效为目标，结合应急物资的不同储运特征，构建不同供应链结构下应急物资调度网络，进行多需求点、多储备点/生产点/协同供给点的供需匹配模式设计。数据集构成要素—需求点位置坐标：以地理坐标系（经度、纬度）来表示各个需求点在地球上的具体位置，这些坐标数据能够精准确定需求点在地理空间上的分布情况，方便规划应急物流的运输路线等操作。各个需求点的需求量：以具体的物资数量单位（如吨、箱等）来衡量每个需求点对应急物资的需求程度，不同物资可分开记录，，数据来源于各地的应急管理部门在过往应急事件处理过程中的统计记录以及现场勘查评估结果，数据量100MB。To address the dynamic scheduling problem of emergency supplies, taking rescue timeliness as the core optimization goal, incorporating the distinct storage and transportation characteristics of various emergency supplies, this work constructs emergency supply scheduling networks under different supply chain architectures, and designs the supply-demand matching models for scenarios with multiple demand points, multiple reserve points, production points, and collaborative supply points. Key elements of the dataset include: 1. Demand point location coordinates: The exact geographic positions of each demand point on Earth are represented via the geographic coordinate system (longitude, latitude). These coordinates can precisely define the geospatial distribution of demand points, which facilitates operations such as planning emergency logistics transportation routes. 2. Demand quantities of each demand point: The demand level of each demand point for emergency supplies is quantified using specific material quantity units (e.g., "tons, boxes, etc."). Different types of supplies can be recorded separately. The data is collected from statistical records and on-site investigation and assessment results of local emergency management departments during past emergency response operations, with a total data size of 100 MB.

搜集汇总

背景与挑战

背景概述

该数据集旨在解决应急物资动态调度问题，以提升救助时效性，通过构建多需求点与多供给点的调度网络进行供需匹配设计。其核心要素包括基于地理坐标系的需求点位置坐标和以物资数量衡量的需求量，数据源自应急管理部门的历史记录与现场勘查，总量约100MB。