Urban deliveries are subject to many access restrictions which creates the need to establish a system of loading bays and to split the last mile delivery into driving and walking parts. A new model based on hard and soft clustering approach is developed by Letnik et. al. to solve the loading bay assignment problem for efficient vehicle routing and walking in last-mile delivery.
The flexibility of the model is provided by the soft clustering approach based on different membership degrees of customers to loading bays. Especially for instances with large numbers of loading bays, soft clustering seems to give better results, it leads to higher flexibility of city logistics systems, minimal driving distances, and adequately short walking paths, which contribute to the goal of reaching sustainable urban freight deliveries.
The total length of average driving and walking distances decreases with the increase in the number of loading bays. The researchers conclude that a soft optimization approach proves to be an acceptable alternative for decreasing driving distances especially for a larger number of loading bays. They, therefore, advise city authorities to plan reasonably large numbers of loading bays in urban areas and to use soft optimization approach when assigning loading bays to the routing of the urban last-mile deliveries.
This would enable them to reduce the number of driven kilometers and create greater flexibility of the city logistics system. Such a system would also have beneficial results for logistics operators, users, and city dwellers, which are constantly looking for a better, more efficient, and sustainable city logistics system.