Journal ArticleDOI
Butterfly optimization algorithm: a novel approach for global optimization
Sankalap Arora,Satvir Singh +1 more
- Vol. 23, Iss: 3, pp 715-734
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TLDR
A new nature-inspired algorithm, namely butterfly optimization algorithm (BOA) that mimics food search and mating behavior of butterflies, to solve global optimization problems and results indicate that the proposed BOA is more efficient than other metaheuristic algorithms.Abstract:
Real-world problems are complex as they are multidimensional and multimodal in nature that encourages computer scientists to develop better and efficient problem-solving methods. Nature-inspired metaheuristics have shown better performances than that of traditional approaches. Till date, researchers have presented and experimented with various nature-inspired metaheuristic algorithms to handle various search problems. This paper introduces a new nature-inspired algorithm, namely butterfly optimization algorithm (BOA) that mimics food search and mating behavior of butterflies, to solve global optimization problems. The framework is mainly based on the foraging strategy of butterflies, which utilize their sense of smell to determine the location of nectar or mating partner. In this paper, the proposed algorithm is tested and validated on a set of 30 benchmark test functions and its performance is compared with other metaheuristic algorithms. BOA is also employed to solve three classical engineering problems (spring design, welded beam design, and gear train design). Results indicate that the proposed BOA is more efficient than other metaheuristic algorithms.read more
Citations
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Journal ArticleDOI
FOX: a FOX-inspired optimization algorithm
TL;DR: In this paper , the authors proposed a novel nature-inspired optimization algorithm called the Fox Optimizer (FOX) which mimics the foraging behavior of foxes in nature when hunting preys.
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Cat Swarm Optimization Algorithm -- A Survey and Performance Evaluation
TL;DR: An in-depth survey and performance evaluation of the Cat Swarm Optimization (CSO) Algorithm is presented and it is confirmed that CSO ranks first on the whole.
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Quantum Chaotic Butterfly Optimization Algorithm With Ranking Strategy for Constrained Optimization Problems
TL;DR: The quantum chaos butterfly optimization algorithm (QCBOA) as mentioned in this paper uses chaos theory and quantum computing techniques to adapt the food foraging and social behaviors of butterflies to improve the performance of butterfly optimization.
Journal ArticleDOI
Improved Manta Ray Foraging Optimization for Parameters Identification of Magnetorheological Dampers
TL;DR: An improved manta ray foraging optimization (IMRFO) is proposed, which designs a searching control factor according to a weak exploration ability of MRFO, which can effectively increase the global exploration of the algorithm.
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Lens-imaging learning Harris hawks optimizer for global optimization and its application to feature selection
TL;DR: Li et al. as discussed by the authors proposed an improved version of HHO, named LIL-HHO, where a modified escaping energy strategy based on sine function for the energy of prey is proposed to achieve a good transition between the exploration phase and exploitation phase.
References
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Journal ArticleDOI
Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces
Rainer Storn,Kenneth Price +1 more
TL;DR: In this article, a new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented, which requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
BookDOI
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
TL;DR: Initially applying his concepts to simply defined artificial systems with limited numbers of parameters, Holland goes on to explore their use in the study of a wide range of complex, naturally occuring processes, concentrating on systems having multiple factors that interact in nonlinear ways.
Journal ArticleDOI
No free lunch theorems for optimization
TL;DR: A framework is developed to explore the connection between effective optimization algorithms and the problems they are solving and a number of "no free lunch" (NFL) theorems are presented which establish that for any algorithm, any elevated performance over one class of problems is offset by performance over another class.
Journal ArticleDOI
Grey Wolf Optimizer
TL;DR: The results of the classical engineering design problems and real application prove that the proposed GWO algorithm is applicable to challenging problems with unknown search spaces.