An algorithm for minimizing clustering functions

DOI10.1080/02331930500096155zbMath1122.90059OpenAlexW2168087308MaRDI QIDQ5317732

Julien Ugon, Adil M. Bagirov

Publication date: 21 September 2005

Published in: Optimization (Search for Journal in Brave)

Full work available at URL: http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/60182

zbMATH Keywords

nonconvex optimizationcluster analysisnonsmoothdiscrete gradient methodclustering functions

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26) Nonsmooth analysis (49J52) Numerical methods based on nonlinear programming (49M37) Discrete approximations in optimal control (49M25)

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Uses Software

• TSPLIB
• J-MEANS

Cites Work

• Unnamed Item
• A comparison of two dual-based procedures for solving the p-median problem
• UOBYQA: unconstrained optimization by quadratic approximation
• Variable neighborhood decomposition search
• A global optimization approach to classification
• Methods of descent for nondifferentiable optimization
• TSPLIB—A Traveling Salesman Problem Library
• A Branch and Bound Clustering Algorithm
• Finding the nearest point in A polytope
• Semismooth and Semiconvex Functions in Constrained Optimization
• Cluster analysis by simulated annealing
• An Interior Point Algorithm for Minimum Sum-of-Squares Clustering
• A Method for Minimization of Quasidifferentiable Functions
• Evaluation of a Branch and Bound Algorithm for Clustering
• A Dynamic Programming Algorithm for Cluster Analysis
• A Simplex Method for Function Minimization
• J-MEANS: A new local search heuristic for minimum sum of squares clustering