A mixed-integer programming approach to the clustering problem with an application in customer segmentation

A mixed-integer programming approach to the clustering problem with an application in customer segmentation

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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: , , ,
Keywords: datamining, programming: integer
Abstract:

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.

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