M.A. (Mathijs) van Zon MSc
PhD Track Splitting the bill of timely transportation
Transportation costs of a delivery route are dependent on the total distance travelled and the time spent on the road. When multiple customers are visited on such a route, it is not at all obvious which customer is responsible for what share of the costs. Customers affect the delivery route in various ways, depending on their location, demand size, and the time window during which they wish to receive their delivery. The research described in this proposal is aimed at developing decision support tools to allocate the costs of a delivery route to the various customers. Note that depending on the application, these costs may be thought of as monetary or emission.
Researchers have in the past years recognized many opportunities for collaboration in transportation. However, in practice such initiatives are hindered by the inability of different parties to share the costs and benefits of such collaborations. To overcome this inability, in this study allocation methods will be developed to allocate costs in a way that is agreeable to all parties involved. This way, the proposed research complements many past and current research projects in this field.
To design such allocation methods, a model will be designed using concepts of cooperative game theory combined with vehicle routing. Special attention will be paid to the inclusion of time windows for delivery at each customer. Considering time windows is vital for the applicability of allocation methods. Although in many applications time windows are present, the limited body of research on cost allocation does not include these.
In the proposed research a general theoretic framework will be developed for cost allocation games. This framework will then be extended for three particular applications They are: intercompany consolidation of transport flows, computing delivery fees charged by e-grocers and allocating CO2 emission.
- Operations Research, Vehicle Routing, Cooperative Game-Theory
- Time frame
- 2017 -
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