Time-dependent routing

Instances for Time-Dependent Routing​

Welcome to our repository of synthetic and realistic instances for time-dependent routing problems. This resource provides valuable data for researchers and practitioners working on various routing problems that consider the time-dependent nature of travel times.Although Time-Dependent Vehicle Routing problems have received increased attention from the scientific community in recent years, there is still a lack of real time-dependent data. Only big IT players (such as Google, Apple, Microsoft, …) have the availability of high-quality historical time-dependent data. As a result, there are no real travel time dataset freely available to the entire research community. To overcome this aspect, most of the literature on Time-Dependent Vehicle Routing problems relies on synthetic travel time functions. As far as synthetic time-dependent data is concerned, we observe that there are (highly-cited) contributions (see for example Ichoua et al. [2003], Hashimoto et al. [2008]) on vehicle routing problems where the computational campaign relies on time-dependent graphs which satisfy the sufficient conditions partially introduced by Cordeau et al. [2014] and further generalized by the path ranking invariance property defined by Adamo et al. in “On path ranking in time-dependent graphs”.Below, you’ll find descriptions of the available instance groups, along with a detailed PDF explaining the formats used.

PDF Description

We have provided a comprehensive PDF document that outlines the formats of the instances available on this page. This guide will help you understand the structure of the data and how to utilize it effectively in your research or applications.

DOWNLOAD PDF 

Instance Groups

  1. Instances from Adamo et al. [2020]:
    • This group includes instances derived from the Time-Dependent Traveling Salesman Problem
    • DOWNLOAD [ sha256 signature 3b7c921de8914dfa5586a88d2539de657b915754112cc64fe0b17d2847a5c608 ]
    • Instance list
  2. Instances from Arigliano et al. [2019]:
    • This group includes instances derived from the Time-Dependent Traveling Salesman Problem with Time Windows
    • DOWNLOAD  [ sha256 signature 76df6bd671a88526ede2fcd44c022807e4c32a63cb2c86533e051c0704b6f777 ]
    • Instance list
  3. Realistic Instances from Ghiani et al. [2020]:
  4. Instances from Vu et al. [2020]:
    • This group includes instances derived from the Time-Dependent Traveling Salesman Problem with Time Windows
    • 60 customers  [ sha256 signature f9c10c194ee0c832429261cd72d12796cb2deae93474dcb2d307c588e240b2cd ]
    • 80 customers  [ sha256 signature 894da52254700d8728aba0bbf2b1180e70878964e7e7e258b9937e9aab96ecd0 ]
    • 100 customers [ sha256 signature 98373baab390825bf401f379ff4c3adc17e669f6ad998358b00117434d2efa09 ]
    • Instance list
We invite you to explore these instances and leverage them in your time-dependent routing research. Download the instances and the accompanying PDF to get started!A quick introduction is available in this Colab notebook Open In Colab

Old datasets

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