A carnivorous plant algorithm for solving global optimization problems
In this study, a novel metaheuristic algorithm, namely, carnivorous plant algorithm (CPA), inspired by how the carnivorous plants adapting to survive in the harsh environment, was proposed. The CPA was first evaluated on thirty well-known benchmark functions with different characteristics and sev...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2021
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/929/1/J11860_1dde0725713aaaf2eb8763ec1131caf5.pdf http://eprints.uthm.edu.my/929/ https://doi.org/10.1016/j.asoc.2020.106833 |
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| Summary: | In this study, a novel metaheuristic algorithm, namely, carnivorous plant algorithm (CPA), inspired
by how the carnivorous plants adapting to survive in the harsh environment, was proposed. The
CPA was first evaluated on thirty well-known benchmark functions with different characteristics and
seven CEC 2017 test functions. Its convergence characteristic and computational time were analysed
and compared with seven widely used metaheuristic algorithms, with the superiority was validated
using the Wilcoxon signed-rank test. The applicability of the CPA was further examined on mechanical
engineering design problems and a real-world challenging application of controlling the orientation of
a five degree-of-freedom robotic arm. Experimental simulations demonstrated the supremacy of the
CPA in solving global optimization problems. |
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