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Journal of Applied Mathematics
Volume 2013, Article ID 380985, 13 pages
Research Article

Generalised Adaptive Harmony Search: A Comparative Analysis of Modern Harmony Search

1Department of Computer Science and Software Engineering, University of Canterbury, Christchurch 8140, New Zealand
2Department of Energy and Information Technology, Gachon University, Seongnam 461-701, Republic of Korea

Received 30 January 2013; Accepted 22 March 2013

Academic Editor: Xin-She Yang

Copyright © 2013 Jaco Fourie et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Harmony search (HS) was introduced in 2001 as a heuristic population-based optimisation algorithm. Since then HS has become a popular alternative to other heuristic algorithms like simulated annealing and particle swarm optimisation. However, some flaws, like the need for parameter tuning, were identified and have been a topic of study for much research over the last 10 years. Many variants of HS were developed to address some of these flaws, and most of them have made substantial improvements. In this paper we compare the performance of three recent HS variants: exploratory harmony search, self-adaptive harmony search, and dynamic local-best harmony search. We compare the accuracy of these algorithms, using a set of well-known optimisation benchmark functions that include both unimodal and multimodal problems. Observations from this comparison led us to design a novel hybrid that combines the best attributes of these modern variants into a single optimiser called generalised adaptive harmony search.