亚马逊雨林
计算机科学
英里
数据集
最后一英里(运输)
标识符
大都市区
集合(抽象数据类型)
数据科学
运输工程
运筹学
地理
工程类
计算机网络
人工智能
生物
考古
程序设计语言
生态学
大地测量学
作者
Daniel Merchán,Jatin Arora,Julian Pachon,Karthik C. Konduri,Matthias Winkenbach,Steven Parks,Joseph Noszek
出处
期刊:Transportation Science
[Institute for Operations Research and the Management Sciences]
日期:2022-09-14
卷期号:58 (1): 8-11
被引量:41
标识
DOI:10.1287/trsc.2022.1173
摘要
The 2021 Amazon Last Mile Routing Research Challenge, hosted by Amazon.com’s Last Mile Research team, and scientifically supported by the Massachusetts Institute of Technology’s Center for Transportation and Logistics, prompted participants to leverage real operational data to find new and better ways to solve a real-world routing problem. In this article, we describe the data set released for the research challenge, which includes route-, stop-, and package-level features for 9,184 historical routes performed by Amazon drivers in 2018 in five metropolitan areas in the United States. This real-world data set excludes any personally identifiable information: all route and package identifiers have been randomly regenerated and related location data have been obfuscated to ensure anonymity. Although multiple synthetic benchmark data sets are available in the literature, the data set of the 2021 Amazon Last Mile Routing Research Challenge is the first large and publicly available data set to include instances based on real-world operational routing data. History: This paper has been accepted for the Transportation Science Special Issue on Machine Learning Methods and Applications in Large-Scale Route Planning Problems.
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