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  • CVRP-pseudopoly

    Rights statement: This is the author’s version of a work that was accepted for publication in European Journal of Operational 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 European Journal of Operational Research, 272, 1, 2019 DOI: 10.1016/j.ejor.2018.06.002

    Accepted author manuscript, 348 KB, PDF document

    Available under license: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

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The capacitated vehicle routing problem: stronger bounds in pseudo-polynomial time

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Published
<mark>Journal publication date</mark>1/01/2019
<mark>Journal</mark>European Journal of Operational Research
Issue number1
Volume272
Number of pages8
Pages (from-to)24–31
Publication StatusPublished
Early online date15/06/18
<mark>Original language</mark>English

Abstract

The Capacitated Vehicle Routing Problem (CVRP) is a classic combinatorial optimization problem for which many heuristics, relaxations and exact algorithms have been proposed. Since the CVRP is NP-hard in the strong sense, a natural research topic is relaxations that can be solved in pseudo-polynomial time. We consider several old and new relaxations of this kind, all of which are based on column generation. We also analyze the effect of adding some known inequalities. Computational experiments demonstrate that the best of our new relaxations yields extremely tight lower bounds.

Bibliographic note

This is the author’s version of a work that was accepted for publication in European Journal of Operational 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 European Journal of Operational Research, 272, 1, 2019 DOI: 10.1016/j.ejor.2018.06.002

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