Variable neighborhood search for harmonic means clustering

DOI10.1016/j.apm.2010.11.032zbMath1219.68129OpenAlexW2002553917MaRDI QIDQ636511

Nenad Mladenović, Abdulrahman Alguwaizani, Pierre Hansen, Eric W. T. Ngai

Publication date: 28 August 2011

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apm.2010.11.032

zbMATH Keywords

clusteringmetaheuristicsunsupervised learningvariable neighborhood searchK-harmonic meansminimum sum of squares

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Related Items

A mixed integer linear programming model and variable neighborhood search for maximally balanced connected partition problem, Clustering cities based on their development dynamics and variable neigborhood search, Variable neighborhood search for the pharmacy duty scheduling problem, New heuristic for harmonic means clustering, Determining the Set of the Most Critical System Components—Optimization Approach, Candidate groups search for K-harmonic means data clustering, Decomposition/Aggregation K-means for Big Data

Uses Software

• TSPLIB
• J-MEANS
• UCI-ml

Cites Work

• An improved column generation algorithm for minimum sum-of-squares clustering
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• \(K\)-harmonic means data clustering with tabu-search method
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• Variable neighborhood search
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• TSPLIB—A Traveling Salesman Problem Library
• An Interior Point Algorithm for Minimum Sum-of-Squares Clustering
• Variable neighborhood search: Principles and applications
• J-MEANS: A new local search heuristic for minimum sum of squares clustering
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