A multiperiod auto-carrier transportation problem with probabilistic future demands

Christian Billing (), Florian Jaehn () and Thomas Wensing ()
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Christian Billing: University of Augsburg, Sustainable Operations and Logistics
Florian Jaehn: Helmut Schmidt University-University of the Federal Armed Forces Hamburg, Management Science and Operations Research
Thomas Wensing: INFORM GmbH

Journal of Business Economics, 2018, vol. 88, issue 7, No 8, 1009-1028

Abstract: 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.

Keywords: Automotive industry; Vehicle routing problem; Case study (search for similar items in EconPapers)
JEL-codes: C61 L62 L91 R41 (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s11573-018-0904-x

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