Sentence examples for customer clustering from inspiring English sources

Customer clustering is an essential step to reduce the complexity of large-scale logistics network optimization.

This paper presents a fuzzy-based customer clustering algorithm with a hierarchical analysis structure to address this issue.

However, due to the heterogeneity and high-dimension of customers' characteristics, the customer clustering problem has not been widely studied.

On the other hand, tactical fleet design and customer clustering decisions are modeled based on a Hub and Spoke cost structure.

Normally, fleet design and customer clustering decisions are made by mid-level logistics managers while network design decision is made independently by high-level logistics managers.

Results from a case study in Anshun, China reveal that the proposed approach outperforms the other three prevailing algorithms to resolve the customer clustering problem.

Since we do not know the number of target items to be tracked (new items may be added to the shopping cart or some previous items are discard by customers at any time, and we also do not know the number of customers), clustering algorithms, such as k-means [12], in which the number of clusters must be known as a priori, thus leading to this kind of clustering algorithm that can not be applied.

In warm weather, customers cluster around small wooden tables on the street.

The screen door slams regularly, and customers cluster around the glass-fronted display case.

Getting plugged in and connected takes relevant customer clusters and puts them in touch with relevant parts of your business.

Customers cluster there, as a manager pressures them to make a choice.