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  • Euclidean-approximation

    Rights statement: This is the author’s version of a work that was accepted for publication in Computers and Operations Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers and Operations Research, 129, 2021 DOI: 10.1016/j.cor.2020.105197

    Accepted author manuscript, 3.88 MB, PDF document

    Embargo ends: 29/06/22

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Vehicle routing on road networks: how good is Euclidean approximation?

Research output: Contribution to journalJournal articlepeer-review

Published
Article number105197
<mark>Journal publication date</mark>1/05/2021
<mark>Journal</mark>Computers and Operations Research
Volume129
Number of pages13
Publication StatusPublished
Early online date29/12/20
<mark>Original language</mark>English

Abstract

Suppose that one is given a Vehicle Routing Problem (VRP) on a road network, but does not have access to detailed information about that network. One could obtain a heuristic solution by solving a modified version of the problem, in which true road distances are replaced with planar Euclidean distances. We test this heuristic, on two different types of VRP, using real road network data for twelve cities across the world. We also give guidelines on the kind of VRP for which this heuristic can be expected to give good results.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Computers and Operations Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers and Operations Research, 129, 2021 DOI: 10.1016/j.cor.2020.105197