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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/5827

Title: Variable neighbourhood search based heuristic for K-harmonic means clustering
Authors: Alguwaizani, Abdulrahman
Advisors: Mladenović, N
Publication Date: 2011
Publisher: Brunel University, School of Information Systems, Computing and Mathematics
Abstract: Although there has been a rapid development of technology and increase of computation speeds, most of the real-world optimization problems still cannot be solved in a reasonable time. Some times it is impossible for them to be optimally solved, as there are many instances of real problems which cannot be addressed by computers at their present speed. In such cases, the heuristic approach can be used. Heuristic research has been used by many researchers to supply this need. It gives a sufficient solution in reasonable time. The clustering problem is one example of this, formed in many applications. In this thesis, I suggest a Variable Neighbourhood Search (VNS) to improve a recent clustering local search called K-Harmonic Means (KHM).Many experiments are presented to show the strength of my code compared with some algorithms from the literature. Some counter-examples are introduced to show that KHM may degenerate entirely, in either one or more runs. Furthermore, it degenerates and then stops in some familiar datasets, which significantly affects the final solution. Hence, I present a removing degeneracy code for KHM. I also apply VNS to improve the code of KHM after removing the evidence of degeneracy.
Description: This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.
URI: http://bura.brunel.ac.uk/handle/2438/5827
Appears in Collections:Brunel University Theses
Mathematical Science
Computer Science
Dept of Mathematics Theses

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