| 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.Thememory consideration and population update aremodified 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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