Cellular Harmony Search for Optimization Problems
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 conc...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2013-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2013/139464 |
| Summary: | 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. |
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| ISSN: | 1110-757X 1687-0042 |