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Journal of Applied Mathematics
Volume 2013, Article ID 139464, 20 pages
Research Article

Cellular Harmony Search for Optimization Problems

1School of Computer Sciences, Universiti Sains Malaysia, 11800 Penang, Malaysia
2Department of Information Technology, Al-Huson University College, Al-Balqa Applied University, P.O. Box 50, Al-Huson, Irbid, Jordan
3Department of Computer Science, Jadara University, P.O. Box 733, Irbid, Jordan

Received 8 July 2013; Revised 15 August 2013; Accepted 16 August 2013

Academic Editor: Zong Woo Geem

Copyright © 2013 Mohammed Azmi Al-Betar 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.


Structured population in evolutionary algorithms (EAs) is an important research track where an individual only interacts with its neighboring individuals in the breeding step. The main rationale behind this is to provide a high level of diversity to overcome the genetic drift. Cellular automata concepts have been embedded to the process of EA in order to provide a decentralized method in order to preserve the population structure. Harmony search (HS) is a recent EA that considers the whole individuals in the breeding step. In this paper, the cellular automata concepts are embedded into the HS algorithm to come up with a new version called cellular harmony search (cHS). In cHS, the population is arranged as a two-dimensional toroidal grid, where each individual in the grid is a cell and only interacts with its neighbors. The memory consideration and population update are modified according to cellular EA theory. The experimental results using benchmark functions show that embedding the cellular automata concepts with HS processes directly affects the performance. Finally, a parameter sensitivity analysis of the cHS variation is analyzed and a comparative evaluation shows the success of cHS.