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Operations research and data mining

Citations

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Cited by:

  1. Blanquero, Rafael & Carrizosa, Emilio & Molero-Río, Cristina & Romero Morales, Dolores, 2020. "Sparsity in optimal randomized classification trees," European Journal of Operational Research, Elsevier, vol. 284(1), pages 255-272.
  2. Geuens, Stijn & Coussement, Kristof & De Bock, Koen W., 2018. "A framework for configuring collaborative filtering-based recommendations derived from purchase data," European Journal of Operational Research, Elsevier, vol. 265(1), pages 208-218.
  3. Clarisse Dhaenens & Laetitia Jourdan, 2022. "Metaheuristics for data mining: survey and opportunities for big data," Annals of Operations Research, Springer, vol. 314(1), pages 117-140, July.
  4. Armend Salihu & Visar Shehu, 2020. "Data Mining Based Classifiers for Credit Risk Analysis," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 18(2 (Summer), pages 147-167.
  5. Koen W. de Bock & Kristof Coussement & Arno De Caigny & Roman Slowiński & Bart Baesens & Robert N Boute & Tsan-Ming Choi & Dursun Delen & Mathias Kraus & Stefan Lessmann & Sebastián Maldonado & David , 2023. "Explainable AI for Operational Research: A Defining Framework, Methods, Applications, and a Research Agenda," Post-Print hal-04219546, HAL.
  6. Salihu, Armend & Shehu, Visar, 2020. "A Review of Algorithms for Credit Risk Analysis," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2020), Virtual Conference, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Virtual Conference, 10-12 September 2020, pages 134-146, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
  7. Tom Pape, 2020. "Prioritising data items for business analytics: Framework and application to human resources," Papers 2012.13813, arXiv.org.
  8. Carrizosa, Emilio & Guerrero, Vanesa & Romero Morales, Dolores, 2019. "Visualization of complex dynamic datasets by means of mathematical optimization," Omega, Elsevier, vol. 86(C), pages 125-136.
  9. Heydari Majeed & Yousefli Amir, 2017. "A new optimization model for market basket analysis with allocation considerations: A genetic algorithm solution approach," Management & Marketing, Sciendo, vol. 12(1), pages 1-11, March.
  10. Asunur Cezar & Srinivasan Raghunathan & Sumit Sarkar, 2020. "Adversarial Classification: Impact of Agents’ Faking Cost on Firms and Agents," Production and Operations Management, Production and Operations Management Society, vol. 29(12), pages 2789-2807, December.
  11. Maurizio Boccia & Antonio Sforza & Claudio Sterle, 2020. "Simple Pattern Minimality Problems: Integer Linear Programming Formulations and Covering-Based Heuristic Solving Approaches," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 1049-1060, October.
  12. Qiao, Wanguan & Liu, Quanlong & Li, Xinchun & Luo, Xixi & Wan, YuLong, 2018. "Using data mining techniques to analyze the influencing factor of unsafe behaviors in Chinese underground coal mines," Resources Policy, Elsevier, vol. 59(C), pages 210-216.
  13. Mark Gilchrist & Deana Lehmann Mooers & Glenn Skrubbeltrang & Francine Vachon, 2012. "Knowledge Discovery in Databases for Competitive Advantage," Journal of Management and Strategy, Journal of Management and Strategy, Sciedu Press, vol. 3(2), pages 2-15, April.
  14. Chunyang Yu & Wei Zhang & Xun Xu & Yangjian Ji & Shiqiang Yu, 2018. "Data mining based multi-level aggregate service planning for cloud manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 29(6), pages 1351-1361, August.
  15. R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.
  16. Saridakis, Charalampos & Katsikeas, Constantine S. & Angelidou, Sofia & Oikonomidou, Maria & Pratikakis, Polyvios, 2023. "Mining Twitter lists to extract brand-related associative information for celebrity endorsement," European Journal of Operational Research, Elsevier, vol. 311(1), pages 316-332.
  17. Matteo Fischetti & Ivana Ljubić & Markus Sinnl, 2017. "Redesigning Benders Decomposition for Large-Scale Facility Location," Management Science, INFORMS, vol. 63(7), pages 2146-2162, July.
  18. Caballini, Claudia & Gracia, Maria D. & Mar-Ortiz, Julio & Sacone, Simona, 2020. "A combined data mining – optimization approach to manage trucks operations in container terminals with the use of a TAS: Application to an Italian and a Mexican port," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
  19. Anzanello, Michel J. & Albin, Susan L. & Chaovalitwongse, Wanpracha A., 2012. "Multicriteria variable selection for classification of production batches," European Journal of Operational Research, Elsevier, vol. 218(1), pages 97-105.
  20. Unler, Alper & Murat, Alper, 2010. "A discrete particle swarm optimization method for feature selection in binary classification problems," European Journal of Operational Research, Elsevier, vol. 206(3), pages 528-539, November.
  21. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
  22. Kaiquan Xu & Stephen Shaoyi Liao & Raymond Y. K. Lau & J. Leon Zhao, 2014. "Effective Active Learning Strategies for the Use of Large-Margin Classifiers in Semantic Annotation: An Optimal Parameter Discovery Perspective," INFORMS Journal on Computing, INFORMS, vol. 26(3), pages 461-483, August.
  23. Zhang, Zhiwang & Gao, Guangxia & Shi, Yong, 2014. "Credit risk evaluation using multi-criteria optimization classifier with kernel, fuzzification and penalty factors," European Journal of Operational Research, Elsevier, vol. 237(1), pages 335-348.
  24. Hauser, Matthias & Flath, Christoph M. & Thiesse, Frédéric, 2021. "Catch me if you scan: Data-driven prescriptive modeling for smart store environments," European Journal of Operational Research, Elsevier, vol. 294(3), pages 860-873.
  25. Clarisse Dhaenens & Laetitia Jourdan, 2019. "Metaheuristics for data mining," 4OR, Springer, vol. 17(2), pages 115-139, June.
  26. Maysam Eftekhary & Peyman Gholami & Saeed Safari & Mohammad Shojaee, 2012. "Ranking Normalization Methods for Improving the Accuracy of SVM Algorithm by DEA Method," Modern Applied Science, Canadian Center of Science and Education, vol. 6(10), pages 1-26, October.
  27. Krzysko, Miroslaw & Wolynski, Waldemar, 2009. "New variants of pairwise classification," European Journal of Operational Research, Elsevier, vol. 199(2), pages 512-519, December.
  28. Scarpel, Rodrigo Arnaldo, 2014. "A demand trend change early warning forecast model for the city of São Paulo multi-airport system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 65(C), pages 23-32.
  29. Filom, Siyavash & Amiri, Amir M. & Razavi, Saiedeh, 2022. "Applications of machine learning methods in port operations – A systematic literature review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
  30. Besseris, George J., 2012. "Profiling effects in industrial data mining by non-parametric DOE methods: An application on screening checkweighing systems in packaging operations," European Journal of Operational Research, Elsevier, vol. 220(1), pages 147-161.
  31. Davidson, Ian & Tayi, Giri, 2009. "Data preparation using data quality matrices for classification mining," European Journal of Operational Research, Elsevier, vol. 197(2), pages 764-772, September.
  32. 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.
  33. Boschetti, Marco A. & Golfarelli, Matteo & Graziani, Simone, 2020. "An exact method for shrinking pivot tables," Omega, Elsevier, vol. 93(C).
  34. Jesse G. Wales & Alexander J. Zolan & William T. Hamilton & Alexandra M. Newman & Michael J. Wagner, 2023. "Combining simulation and optimization to derive operating policies for a concentrating solar power plant," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 119-150, March.
  35. J Yang & S Ólafsson, 2009. "Near-optimal feature selection for large databases," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(8), pages 1045-1055, August.
  36. Amaldi, Edoardo & Coniglio, Stefano, 2013. "A distance-based point-reassignment heuristic for the k-hyperplane clustering problem," European Journal of Operational Research, Elsevier, vol. 227(1), pages 22-29.
  37. Lessmann, Stefan & Voß, Stefan, 2009. "A reference model for customer-centric data mining with support vector machines," European Journal of Operational Research, Elsevier, vol. 199(2), pages 520-530, December.
  38. Qing Yang & Yanxia Zhu & Xingxing Liu & Lingmei Fu & Qianqian Guo, 2019. "Bayesian-Based NIMBY Crisis Transformation Path Discovery for Municipal Solid Waste Incineration in China," Sustainability, MDPI, vol. 11(8), pages 1-21, April.
  39. Du, Yu & Lin, Xiaodong & Pham, Minh & Ruszczyński, Andrzej, 2021. "Selective linearization for multi-block statistical learning," European Journal of Operational Research, Elsevier, vol. 293(1), pages 219-228.
  40. Ramli, Azizul Azhar & Watada, Junzo & Pedrycz, Witold, 2011. "Real-time fuzzy regression analysis: A convex hull approach," European Journal of Operational Research, Elsevier, vol. 210(3), pages 606-617, May.
  41. necula, sabina-cristiana & Radu, Laura-Diana, 2011. "Decision Support Systems Usefulness and A Practical Solution Based on Semantic Web Technologies," MPRA Paper 51547, University Library of Munich, Germany.
  42. Daniel Gartner & Yiye Zhang & Rema Padman, 2018. "Cognitive workload reduction in hospital information systems," Health Care Management Science, Springer, vol. 21(2), pages 224-243, June.
  43. Carrizosa, Emilio & Guerrero, Vanesa & Romero Morales, Dolores, 2018. "On Mathematical Optimization for the visualization of frequencies and adjacencies as rectangular maps," European Journal of Operational Research, Elsevier, vol. 265(1), pages 290-302.
  44. De Bock, Koen W. & Coussement, Kristof & Caigny, Arno De & Słowiński, Roman & Baesens, Bart & Boute, Robert N. & Choi, Tsan-Ming & Delen, Dursun & Kraus, Mathias & Lessmann, Stefan & Maldonado, Sebast, 2024. "Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda," European Journal of Operational Research, Elsevier, vol. 317(2), pages 249-272.
  45. Mareček, Jakub & Richtárik, Peter & Takáč, Martin, 2017. "Matrix completion under interval uncertainty," European Journal of Operational Research, Elsevier, vol. 256(1), pages 35-43.
  46. 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.
  47. 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.
  48. Arnaldo Scarpel, Rodrigo & Pelicioni, Luciele Cristina, 2018. "A data analytics approach for anticipating congested days at the São Paulo International Airport," Journal of Air Transport Management, Elsevier, vol. 72(C), pages 1-10.
  49. Cassioli, A. & Chiavaioli, A. & Manes, C. & Sciandrone, M., 2013. "An incremental least squares algorithm for large scale linear classification," European Journal of Operational Research, Elsevier, vol. 224(3), pages 560-565.
  50. 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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