Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/209293 
Year of Publication: 
2015
Citation: 
[Editor:] Blecker, Thorsten [Editor:] Kersten, Wolfgang [Editor:] Ringle, Christian M. [Title:] Operational Excellence in Logistics and Supply Chains: Optimization Methods, Data-driven Approaches and Security Insights. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 22 [ISBN:] 978-3-7375-4058-2 [Publisher:] epubli GmbH [Place:] Berlin [Year:] 2015 [Pages:] 391-418
Publisher: 
epubli GmbH, Berlin
Abstract: 
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.
Subjects: 
Driver Experience Feedback
Geocoding Correction
Real Truck Tours
Address Matching
Creative Commons License: 
cc-by-sa Logo
Document Type: 
Conference Paper

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