Data coverage
The 2021 Amazon Last Mile Routing Research Challenge was an innovative research initiative led by Amazon.com and supported by the Massachusetts Institute of Technology’s Center for Transportation and Logistics. Over a period of 4 months, participants were challenged to develop innovative machine learning-based methods to enhance classic optimization-based approaches to solve the travelling salesperson problem, by learning from historical routes executed by Amazon delivery drivers. The primary goal of the Amazon Last Mile Routing Research Challenge was to foster innovative applied research in route planning, building on recent advances in predictive modeling, and using a real-world problem and data. The dataset released for the research challenge 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 dataset 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 datasets are available in the literature, the dataset of the 2021 Amazon Last Mile Routing Research Challenge is the first large and publicly available dataset to include instances based on real-world operational routing data. The dataset is fully described and formally introduced in the following Transportation Science article: https://pubsonline.informs.org/doi/10.1287/trsc.2022.1173
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Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. The material for the Amazon Last Mile Routing Research Challenge is provided under a Creative Commons Attribution-NonCommercial 4.0 International Public License (the “License”). You may not use this material except in compliance with the License. You may obtain a copy of the License at: https://creativecommons.org/licenses/by-nc/4.0/legalcode.txt
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