Global manufacturing supply chains may link subsequent production facilities by intermodal transport operations, which are characterised by long transport times, scarce transport capacities and a given time table. Consequently only an integrated scheduling of production and intermodal transport operations may be able to materialise the competitive advantage of such a supply chain in terms of total cost and on time delivery reliability. The execution of this planning task is challenging for both supply chain professionals and scientists, since the underlying planning problem is NP-hard. This paper details a new methodological approach for solving integrated production and transport scheduling problems based on a graph, which allows a reformulation of the scheduling problem as a shortest path problem for each job, which can be solved in polynomial time. The proposed method is applied to a supply chain scenario, which contains a manufacturing facility in Brazil and shipments to customers in Germany. The obtained results show that the approach is suitable for the scheduling of large-scale problems and can be flexibly adapted to different real-world scenarios.
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