Journal of Business Economics

, Volume 88, Issue 7–8, pp 971–1007 | Cite as

Multi-item single-source ordering with detailed consideration of transportation capacities

  • Martin GrunewaldEmail author
  • Thomas Volling
  • Christoph Müller
  • Thomas S. Spengler
Original Paper


We consider multi-item single-source ordering with detailed consideration of transportation capacities. Such problems are characteristic for companies which operate direct links as part of their supply chain to transport loads with heterogeneous physical dimensions and fluctuating demands. Given knowledge on transportation demands, companies can eliminate future transports by shifting the load to fill the inflexible capacity of prior transports. While reducing transportation costs, doing so will ceteris paribus imply inventory. The problem is to coordinate orders across multiple items such that transport costs are minimized at minimal increase in inventory. The approach is distinct from prior works in that it considers detailed loading restrictions. We therefore interpret the problem as a multi-period version of the container loading problem. A wall building approach is used and incorporated into a heuristic rolling horizon procedure. We test the proposed procedure on some random problems which resemble a real inbound case from the automotive industry. As compared to period-by-period planning and two benchmarks with aggregated capacity models from the literature and practice, cost savings are possible under a wide range of operating conditions and mostly independent of the shipping volume. The largest potential exists for mid- to long-distance transports. There is a relevant potential to improve short-distance transports as well, however, only if inventory cost rates are moderate.


Joint ordering Multi-item dynamic lot-sizing Direct links Container loading Automotive industry 

JEL Classification



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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute of Automotive Management and Industrial ProductionTechnische Universität BraunschweigBraunschweigGermany
  2. 2.Faculty of Economics and ManagementTechnische Universität BerlinBerlinGermany

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