This work investigates the parallelization of the Artificial Bee Colony Algorithm. Besides a sequential version enhanced with local search, we compare three parallel models: master-slave, multi-hive with migrations, and hybrid hierarchical. Extensive experiments were done using three numerical benchmark functions with a high number of variables. Statistical results indicate that intensive local search improves the quality of solutions found and, thanks to the coevolution effect, the multi-population approaches obtain better quality with less computational effort. A final comparison between models was done analyzing the trade-offs between quality of solution and processing time.
CITATION STYLE
Parpinelli, R. S., Benitez, C. M. V., & Lopes, H. S. (2011). Parallel Approaches for the Artificial Bee Colony Algorithm (pp. 329–345). https://doi.org/10.1007/978-3-642-17390-5_14
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