Line Haul Planning- DB Schenker
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DB Schenker Benelux
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DB Schenker is the world’s leading global logistics provider — we support industry and trade in the global exchange of goods through land transport, worldwide air and ocean freight, contract logistics and supply chain management. Integrated logistics resides at the world’s most important intersections, where the flow of goods creates an effective link between carriers. Our value-added services ensure the flow of goods continues seamlessly and supply chains stay lean and optimized for success. Our business holds top positions in automotive, technology, consumer goods, trade fair logistics, special transports, and special events logistics.
DB Schenker uses a hub-and-spoke network for distribution, in which freight is collected and sent to local warehouses. It is consolidated in a local warehouse and sent to other local warehouses internationally via line-haul trucks that drive on a schedule. From the destination local warehouses, the freight is distributed again.
This assignment concerns the planning of the line-haul trucks. Although these trucks drive on a schedule, it is possible that the schedules are disrupted, or additional trucks are needed. For example, every night there is a truck from the Netherlands to Spain. However, due to traffic congestion, strikes, or a higher freight demand than usual, it is possible that the truck is not in the Netherlands on time to do the transport, or an additional truck is needed to carry the additional demand.
DB Schenker is looking to develop a decision support system (with AI) that supports planners in taking decisions regarding the planning of their line-haul trucks. This could be by adjusting, increasing, or decreasing their capacity planning.
Research goal and questions
Against this background, the goal of the project is to:
develop a decision support system that advises on planning of line-haul trucks
In particular, we aim to answer the following research questions:
- What situations can occur that disrupt the line-haul schedule?
- What decisions can be taken to handle the disruptions?
- How can a decision support system help to take the best decision each situation?
- How good are the decisions that are made by the system, compared to benchmark decisions?
The assignment will be performed based on historical data on disruptions that occurred and decisions that were taken when a disruption occurred.
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