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

@article{citeulike:5827390, 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.}, author = {Saglam, B. and Salman, F. and Sayin, S. and Turkay, M.}, citeulike-article-id = {5827390}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.ejor.2005.04.048}, citeulike-linkout-1 = {http://linkinghub.elsevier.com/retrieve/pii/S0377221705006879}, day = {16}, doi = {10.1016/j.ejor.2005.04.048}, issn = {03772217}, journal = {European Journal of Operational Research}, keywords = {algorithm, clustering, operations-research, optimization}, month = {September}, number = {3}, pages = {866--879}, posted-at = {2009-10-16 19:01:23}, priority = {4}, title = {A mixed-integer programming approach to the clustering problem with an application in customer segmentation}, url = {http://dx.doi.org/10.1016/j.ejor.2005.04.048}, volume = {173}, year = {2006} }

TY - JOUR ID - citeulike:5827390 L3 - citeulike-article-id:5827390 N2 - 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. IS - 3 JF - European Journal of Operational Research SN - 03772217 EP - 879 TI - A mixed-integer programming approach to the clustering problem with an application in customer segmentation VL - 173 SP - 866 KW - algorithm KW - clustering KW - operations-research KW - optimization AU - Saglam, B AU - Salman, F AU - Sayin, S AU - Turkay, M PY - 2006/09/16/ UR - http://dx.doi.org/10.1016/j.ejor.2005.04.048 ER -