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A Methodology to Determine the Most Cost-Efficient Capacity of CoolblueBikes : Machine learning models to support capacity decisions at the tactical level in delivery routing problems
Heesterman, S.L. (2023) A Methodology to Determine the Most Cost-Efficient Capacity of CoolblueBikes : Machine learning models to support capacity decisions at the tactical level in delivery routing problems.
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| Abstract: | We conduct this research at CoolblueBikes, the bike delivery network of Coolblue. CoolblueBikes is an overflow carrier. Therefore, they can select which potential orders they want to deliver with the available capacity, and decide which remaining orders they want to outsource to delivery partners. However, they do not know what the optimal capacity is to deploy such that they can deliver the optimal number of orders that they are going to select. Therefore, we develop a solution methodology that supports capacity deployment decisions at the tactical level in delivery routing problems. |
| Item Type: | Essay (Master) |
| Clients: | Coolblue, Rotterdam, Netherlands |
| Faculty: | BMS: Behavioural, Management and Social Sciences |
| Subject: | 31 mathematics, 50 technical science in general |
| Programme: | Industrial Engineering and Management MSc (60029) |
| Link to this item: | https://purl.utwente.nl/essays/94719 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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