"warehouse dataset"

"This dataset, denoted as \ud835\udc7e_data, represents a synthetic yet structurally authentic warehouse management dataset comprising 4,132 records and 11 well-defined attributes. It was generated using the Gretel.ai platform, following the structural standards provided by the TI Supply Chain API\u2013Storage Locations specification. The dataset encapsulates essential operational and spatial parameters of warehouses, including unique identifiers, geospatial coordinates, storage capacities, and categorical capacity statuses. Each warehouse entry includes derived metrics such as squared coordinates and storage utilization rates, supporting comprehensive spatial and efficiency analyses. Designed to facilitate research in warehouse optimization, logistics planning, supply chain analytics, and resource allocation, this clean, well-balanced dataset reflects realistic attribute distributions and interdependencies. It is ideally suited for benchmarking algorithms in logistics optimization, classification, clustering, and spatial modeling tasks in industrial and academic applications."

本数据集记为𝔻_data，是一款合成生成但结构高度贴合真实场景的仓储管理数据集，共包含4132条记录与11个明确定义的属性。本数据集依托Gretel.ai平台生成，严格遵循TI供应链API-存储位置规范所设定的结构标准。该数据集涵盖了仓储运营与空间维度的核心参数，包括唯一标识符、地理空间坐标、存储容量以及分类化容量状态。每条仓储条目均包含衍生指标，例如坐标平方值与仓储利用率，可支撑全面的空间分析与效率评估工作。本数据集旨在为仓储优化、物流规划、供应链分析以及资源分配领域的研究提供支持，其数据干净规整、分布均衡，能够反映真实的属性分布与相互依赖关系。该数据集非常适合作为工业与学术场景中，物流优化、分类、聚类以及空间建模等任务的算法基准测试数据集。

搜集汇总

背景与挑战

背景概述

该数据集是一个合成但结构真实的仓库管理数据集，包含4,132条记录和11个属性，基于TI Supply Chain API–Storage Locations规范生成。它涵盖了仓库的唯一标识符、地理坐标、存储容量和容量状态等关键参数，旨在支持仓库优化、物流规划和供应链分析等研究，适用于分类、聚类和空间建模等多种机器学习任务。