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 seven...

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Vydáno v:Applied soft computing Ročník 98; s. 106833
Hlavní autoři: Ong, Kok Meng, Ong, Pauline, Sia, Chee Kiong
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.01.2021
Témata:
Carnivorous plant algorithm
Metaheuristic algorithm
Optimization
Population-based algorithm
Robotic arm
Robotic arm
Carnivorous plant algorithm
Metaheuristic algorithm
Optimization
Population-based algorithm
ISSN:1568-4946, 1872-9681
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Shrnutí: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. •We propose a novel carnivorous plant algorithm (CPA) for global optimization.•Its effectiveness is evaluated in a series of benchmark test functions.•It is also tested in several mechanical design, CEC2011 and robotic arm problems.•Performance comparison with other state-of-the-art methods and CEC winners is made.•The convergence rate and stability of the proposed CPA are better than others.
ISSN:1568-4946
1872-9681
DOI:10.1016/j.asoc.2020.106833