The Firefly Optimization Algorithm: Convergence Analysis and Parameter Selection
نویسندگان
چکیده
منابع مشابه
The Firefly Optimization Algorithm: Convergence Analysis and Parameter Selection
The bio-inspired optimization techniques have obtained great attention in recent years due to its robustness, simplicity and efficiency to solve complex optimization problems. The firefly Optimization (FA or FFA) algorithm is an optimization method with these features. The algorithm is inspired by the flashing behavior of fireflies. In the algorithm, randomly generated solutions will be conside...
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As a nature-inspired search algorithm, firefly algorithm (FA) has several control parameters, which may have great effects on its performance. In this study, we investigate the parameter selection and adaptation strategies in a modified firefly algorithm - adaptive firefly algorithm (AdaFa). There are three strategies in AdaFa including (1) a distance-based light absorption coefficient; (2) a g...
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Meta-heuristic algorithms prove to be competent in outperforming deterministic algorithms for real-world optimization problems. Firefly algorithm is one such recently developed algorithm inspired by the flashing behavior of fireflies. In this work, a detailed formulation and explanation of the Firefly algorithm implementation is given. Later Firefly algorithm is verified using six unimodal engi...
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Nature-inspired algorithms such as Particle Swarm Optimization and Firefly Algorithm are among the most powerful algorithms for optimization. In this paper, we intend to formulate a new metaheuristic algorithm by combining Lévy flights with the search strategy via the Firefly Algorithm. Numerical studies and results suggest that the proposed Lévy-flight firefly algorithm is superior to existing...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2013
ISSN: 0975-8887
DOI: 10.5120/11826-7528