License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.09261.8
URN: urn:nbn:de:0030-drops-21892
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2009/2189/
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Gendron, Bernard ; Khuong, Paul-Virak ; Semet, Frédéric

Formulations, Bounds and Heuristic Methods for a Two-Echelon Adaptive Location-Distribution Problem

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Abstract

We consider a two-echelon location-distribution problem arising from an actual application in fast delivery service. This problem belongs to the class of adaptive logistics problems, as the locations of the facilities (typically, parking spaces) are revised on a daily basis according to demand variations. We present and compare two formulations for this problem: an arc-based model and a path-based model. Since these formulations cannot be solved in reasonable time for large-scale instances, we introduce a heuristic method based on a variable neighborhood search approach.

BibTeX - Entry

@InProceedings{gendron_et_al:DagSemProc.09261.8,
  author =	{Gendron, Bernard and Khuong, Paul-Virak and Semet, Fr\'{e}d\'{e}ric},
  title =	{{Formulations, Bounds and Heuristic Methods for a Two-Echelon Adaptive Location-Distribution Problem}},
  booktitle =	{Models and Algorithms for Optimization in Logistics},
  pages =	{1--3},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9261},
  editor =	{Cynthia Barnhart and Uwe Clausen and Ulrich Lauther and Rolf H. M\"{o}hring},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2009/2189},
  URN =		{urn:nbn:de:0030-drops-21892},
  doi =		{10.4230/DagSemProc.09261.8},
  annote =	{Keywords: Two-echelon location problem, formulations, relaxations, variable neighborhood search}
}

Keywords: Two-echelon location problem, formulations, relaxations, variable neighborhood search
Collection: 09261 - Models and Algorithms for Optimization in Logistics
Issue Date: 2009
Date of publication: 02.10.2009

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