Article ID: | iaor20084034 |
Country: | Netherlands |
Volume: | 173 |
Issue: | 3 |
Start Page Number: | 866 |
End Page Number: | 879 |
Publication Date: | Sep 2006 |
Journal: | European Journal of Operational Research |
Authors: | Sayn Serpil, Salman F. Sibel, Trkay Metin, Salam Burcu |
Keywords: | datamining, programming: integer |
This paper presents a mathematical programming based clustering approach that is applied to a digital platform company's customer segmentation problem involving demographic and transactional attributes related to the customers. The clustering problem is formulated as a mixed-integer programming problem with the objective of minimizing the maximum cluster diameter among all clusters. In order to overcome issues related to computational complexity of the problem, we developed a heuristic approach that improves computational times dramatically without compromising from optimality in most of the cases that we tested. The performance of this approach is tested on a real problem. The analysis of our results indicates that our approach is computationally efficient and creates meaningful segmentation of data.