A new nonsmooth optimization algorithm for minimum sum-of-squares clustering problems

Title: A new nonsmooth optimization algorithm for minimum sum-of-squares clustering problems
Creator: Bagirov, Adil; Yearwood, John
Date: 2006
Type: Text; Journal article
Identifier: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/41992
Identifier: vital:86
Identifier: https://doi.org/doi:10.1016/j.ejor.2004.06.014
Identifier: ISSN:0377-2217
Abstract: The minimum sum-of-squares clustering problem is formulated as a problem of nonsmooth, nonconvex optimization, and an algorithm for solving the former problem based on nonsmooth optimization techniques is developed. The issue of applying this algorithm to large data sets is discussed. Results of numerical experiments have been presented which demonstrate the effectiveness of the proposed algorithm. © 2004 Elsevier B.V. All rights reserved.; C1
Publisher: Elsevier
Relation: European Journal of Operational Research Vol. 170, no. 2 (2006), p. 578-596
Rights: Copyright Elsevier
Rights: This metadata is freely available under a CCO license
Subject: 0102 Applied Mathematics; Search; Minimization; Branch
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