2026-05-23T06:46:30Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/84772024-01-26T01:05:26Zcom_10259_4249com_10259_5086com_10259_2604col_10259_4250

Pacheco Bonrostro, Joaquín Valencia García, Olga 2024-01-25T12:13:05Z 2024-01-25T12:13:05Z 2003-06 0167-9473 http://hdl.handle.net/10259/8477 10.1016/S0167-9473(02)00224-4 A series of metaheuristic algorithms is proposed and analyzed for the non-hierarchical clustering problem under the criterion of minimum sum-of-squares clustering. These algorithms incorporate genetic operators and local search and tabu search procedures. The aim is to obtain quality solutions with short computation times. A series of computational experiments has been performed. The proposed algorithms obtain better results than previously reported methods, especially with a small number of clusters. application/pdf eng Elsevier Computational Statistics & Data Analysis. 2003, V. 43, n. 2, p. 235-248 https://doi.org/10.1016/S0167-9473(02)00224-4 Clusterization Metaheuristics Tabu search Genetic algorithms Memetic algorithms Hybrid algorithms Estadística matemática Mathematical statistics Design of hybrids for the minimum sum-of-squares clustering problem info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/closedAccess Computational Statistics & Data Analysis 43 2 235 248