A multiperiod auto-carrier transportation problem with probabilistic future demands
Publication date
2018-04-04
Document type
Forschungsartikel
Author
Organisational unit
Scopus ID
Publisher
Springer
Series or journal
Journal of Business Economics
ISSN
Periodical volume
88
Periodical issue
7-8
First page
1009
Last page
1028
Peer-reviewed
✅
Part of the university bibliography
✅
Language
English
Keyword
Automotive industry
Case study
Vehicle routing problem
Abstract
In this paper we study the problem of delivering finished vehicles from a logistics yard to dealer locations at which they are sold. The requests for cars arrive dynamically and are not announced in advance to the logistics provider who is granted a certain time-span until which a delivery has to be fulfilled. In a real-world setting, the underlying network is relatively stable in time, since it is usually a rare event that a new dealership opens or an existing one terminates its service. Therefore, probabilities for incoming requests can be derived from historical data. The study explores the potential of using such probabilities to improve the day-to-day decision of sending out or postponing cars that are ready for delivery. Apart from the order selection, we elaborate a heuristic to optimize delivery routes for the selected vehicles, whereby special loading constraints are considered to meet the particular constraints of car transportation via road. In a case study, we illustrate the value of introducing probabilistic information to the planning process and compare the quality of different configurations of our approach.
Version
Published version
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