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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
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