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

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  • Saglam, Burcu
  • Salman, F. Sibel
  • Sayin, Serpil
  • Turkay, Metin

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  • Saglam, Burcu & Salman, F. Sibel & Sayin, Serpil & Turkay, Metin, 2006. "A mixed-integer programming approach to the clustering problem with an application in customer segmentation," European Journal of Operational Research, Elsevier, vol. 173(3), pages 866-879, September.
    • Handle: RePEc:eee:ejores:v:173:y:2006:i:3:p:866-879
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    References listed on IDEAS

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    1. P. S. Bradley & Usama M. Fayyad & O. L. Mangasarian, 1999. "Mathematical Programming for Data Mining: Formulations and Challenges," INFORMS Journal on Computing, INFORMS, vol. 11(3), pages 217-238, August.
    2. Balaji Padmanabhan & Alexander Tuzhilin, 2003. "On the Use of Optimization for Data Mining: Theoretical Interactions and eCRM Opportunities," Management Science, INFORMS, vol. 49(10), pages 1327-1343, October.
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    Cited by:

    1. Calvino, José J. & López-Haro, Miguel & Muñoz-Ocaña, Juan M. & Puerto, Justo & Rodríguez-Chía, Antonio M., 2022. "Segmentation of scanning-transmission electron microscopy images using the ordered median problem," European Journal of Operational Research, Elsevier, vol. 302(2), pages 671-687.
    2. Chagas, Guilherme Oliveira & Lorena, Luiz Antonio Nogueira & dos Santos, Rafael Duarte Coelho, 2022. "A hybrid heuristic for overlapping community detection through the conductance minimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    3. Andrew C. Trapp & Wen Liu & Soussan Djamasbi, 2019. "Identifying Fixations in Gaze Data via Inner Density and Optimization," INFORMS Journal on Computing, INFORMS, vol. 31(3), pages 459-476, July.
    4. Roy Cerqueti & Paolo Falbo & Cristian Pelizzari & Federica Ricca & Andrea Scozzari, 2017. "A mixed integer linear program to compress transition probability matrices in Markov chain bootstrapping," Annals of Operations Research, Springer, vol. 248(1), pages 163-187, January.
    5. Meisel, Stephan & Mattfeld, Dirk, 2010. "Synergies of Operations Research and Data Mining," European Journal of Operational Research, Elsevier, vol. 206(1), pages 1-10, October.
    6. Falah Alhameli & Ali Ahmadian & Ali Elkamel, 2021. "Multiscale Decision-Making for Enterprise-Wide Operations Incorporating Clustering of High-Dimensional Attributes and Big Data Analytics: Applications to Energy Hub," Energies, MDPI, vol. 14(20), pages 1-17, October.
    7. K F Lam, 2010. "In the determination of weight sets to compute cross-efficiency ratios in DEA," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(1), pages 134-143, January.
    8. Emelogu, Adindu & Chowdhury, Sudipta & Marufuzzaman, Mohammad & Bian, Linkan & Eksioglu, Burak, 2016. "An enhanced sample average approximation method for stochastic optimization," International Journal of Production Economics, Elsevier, vol. 182(C), pages 230-252.
    9. Harun Pirim & Burak Eksioglu & Fred W. Glover, 2018. "A Novel Mixed Integer Linear Programming Model for Clustering Relational Networks," Journal of Optimization Theory and Applications, Springer, vol. 176(2), pages 492-508, February.
    10. Corne, David & Dhaenens, Clarisse & Jourdan, Laetitia, 2012. "Synergies between operations research and data mining: The emerging use of multi-objective approaches," European Journal of Operational Research, Elsevier, vol. 221(3), pages 469-479.
    11. Chen, Albert Y. & Yu, Ting-Yi, 2016. "Network based temporary facility location for the Emergency Medical Services considering the disaster induced demand and the transportation infrastructure in disaster response," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 408-423.
    12. Emilio Carrizosa & Vanesa Guerrero & Dolores Romero Morales, 2023. "On mathematical optimization for clustering categories in contingency tables," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 17(2), pages 407-429, June.
    13. Gambella, Claudio & Ghaddar, Bissan & Naoum-Sawaya, Joe, 2021. "Optimization problems for machine learning: A survey," European Journal of Operational Research, Elsevier, vol. 290(3), pages 807-828.

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