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Title: Variable neighbourhood search based heuristic for K-harmonic means clustering
Author: Al-Guwaizani, Abdulrahman
ISNI:       0000 0004 2707 0068
Awarding Body: Brunel University
Current Institution: Brunel University
Date of Award: 2011
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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.
Supervisor: Mladenović, N. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available