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2021 Amazon Last Mile Routing Research Challenge Dataset analytics deep learning geospatial last mile logistics machine learning optimization routing transportation urban


The 2021 Amazon Last Mile Routing Research Challenge was an innovative research initiative led by 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.

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Copyright, 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:


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How to Cite

2021 Amazon Last Mile Routing Research Challenge Dataset was accessed on DATE from Merchan, Daniel; Pachon, Julian; Arora, Jatin; Konduri, Karthik; Winkenbach, Matthias; Parks, Steven; Noszek, Joseph. (2022). Seattle:

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Resources on AWS

  • Description
    Dataset including training and testing data. Folder almrrc2021_data_training includes 6,112 historical routes used for model traning; folder almrrc2021_data_evaluation includes 3072 historical routes used for model evaluation. All routes correspond to year 2018. Please refer to the documentation for details on folder and data structure (
    Resource type
    S3 Bucket
    Amazon Resource Name (ARN)
    AWS Region
    AWS CLI Access (No AWS account required)
    aws s3 ls --no-sign-request s3://amazon-last-mile-challenges/

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