I am looking for references that used customer aggregation to solve large-scale Vehicle Routing Problems. By aggregation, I mean clustering the customers together and representing them with one node in the network. I found some related studies but they are not exactly what I am looking for.
1- I am aware of cluster-first route-second methods to solve the VRP however, these approaches normally cluster the customers to be visited by one vehicle and then solve a TSP for each cluster. What I want is the cases that the vehicle's capacity is enough to visit multiple clusters and a VRP should be solved after the clustering.
2- Clustered vehicle routing problem (CLuVRP), in which customers are grouped into predefined clusters, and all customers in a cluster must be served consecutively by the same vehicle. This is the closest problem to what I am looking for except that I aim to use clustering to scale down the problem search space and most proposed approaches for CLuVRP won't do that.
3- Districting for VRP, these types of studies focus on building the districts (clusters) not the routing decisions or questions such as how to calculate the parameters (e.g. distances and time windows for an aggregated network), how to find the actual sequence of the customers after finding the sequence of clusters.
4- I only was able to found two studies by A. Campbell that use customer clustering to reduce the size of VRP.
- "Aggregation for the probabilistic traveling salesman problem"
- "Runtime reduction techniques for the probabilistic traveling salesman problem with deadlines"
Surprisingly, I couldn't find more references on this. If you know any relevant sources I would be grateful if you could share them.