Konferenzbeitrag

Address Matching Using Truck Tours Feedback

When researchers or logistics software developers deal with vehicle routing optimization, they mainly focus on minimizing the total traveled distance or time of the tours, and maximizing the number of visited customers. However, in real transporter situations, the actual data received is often of bad quality, particularly the irrelevance of addresses and address geocoding errors. Therefore, trying to optimize tours with impertinent customers' GPS-coordinates, which are the most important input data for solving a vehicle routing problem, will lead to an incoherent solution, especially if the locations of the customers used for the optimization are very different from their real positions. Our work is supported by a logistics software editor Tedies (2013) and a transport company Upsilon (2009). We work with the company's real truck routes data to carry our experiments. The aim of this work is to use the experience of the driver and the feedback of the real truck tours to validate and correct GPS-coordinates to the next tours. Our method significantly improves the quality of the geocoding. This study shows the importance of taking into account the feedback of the trucks to gradually correct address geocoding errors. Indeed, the accuracy of customer's address and its GPS-coordinates plays a major role in tours optimization. This feedback is naturally and usually taken into account by transporters (by asking drivers, calling customers, …), to learn about their tours and bring corrections to the upcoming tours. Hence, we develop a method to do most of that automatically.

Sprache
Englisch

Erschienen in
10419/209191

Klassifikation
Management
Thema
Driver Experience Feedback
Geocoding Correction
Real Truck Tours
Address Matching

Ereignis
Geistige Schöpfung
(wer)
Bouallouche, Dalicia
Vioix, Jean-Baptiste
Millot, Stéphane
Busvelle, Eric
Ereignis
Veröffentlichung
(wer)
epubli GmbH
(wo)
Berlin
(wann)
2015

Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Konferenzbeitrag

Beteiligte

  • Bouallouche, Dalicia
  • Vioix, Jean-Baptiste
  • Millot, Stéphane
  • Busvelle, Eric
  • epubli GmbH

Entstanden

  • 2015

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