Journal
APPLIED SCIENCES-BASEL
Volume 9, Issue 10, Pages -Publisher
MDPI
DOI: 10.3390/app9101973
Keywords
compact bat algorithm; wireless sensor networks; swarm intelligence; unequal clustering
Categories
Funding
- Natural Science Foundation of Fujian Province [2018J01638]
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Everyday, a large number of complex scientific and industrial problems involve finding an optimal solution in a large solution space. A challenging task for several optimizations is not only the combinatorial operation but also the constraints of available devices. This paper proposes a novel optimization algorithm, namely the compact bat algorithm (cBA), to use for the class of optimization problems involving devices which have limited hardware resources. A real-valued prototype vector is used for the probabilistic operations to generate each candidate for the solution of the optimization of the cBA. The proposed cBA is extensively evaluated on several continuous multimodal functions as well as the unequal clustering of wireless sensor network (uWSN) problems. Experimental results demonstrate that the proposed algorithm achieves an effective way to use limited memory devices and provides competitive results.
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