An accurate partially attracted firefly algorithm
The firefly algorithm (FA) is a new and powerful algorithm for optimization. However, it has the disadvantages of high computational complexity and low convergence accuracy, especially when solving complex problems. In this paper, an accurate partially attracted firefly algorithm (PaFA) is proposed...
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sg-ntu-dr.10356-1390392020-05-15T02:30:55Z An accurate partially attracted firefly algorithm Zhou, Lingyun Ding, Lixin Ma, Maode Tang, Wan School of Electrical and Electronic Engineering Engineering::Computer science and engineering Firefly Algorithm Partial Attraction Model The firefly algorithm (FA) is a new and powerful algorithm for optimization. However, it has the disadvantages of high computational complexity and low convergence accuracy, especially when solving complex problems. In this paper, an accurate partially attracted firefly algorithm (PaFA) is proposed by adopting a partial attraction model and a fast attractiveness calculation strategy. The partial attraction model can preserve swarm diversity and make full use of individual information. The fast attractiveness calculation strategy ensures information sharing among the individuals and it also improves the convergence accuracy. The experimental results demonstrate the good performance of PaFA in terms of the solution accuracy compared with two state-of-the-art FA variants and two other bio-inspired algorithms. 2020-05-15T02:30:55Z 2020-05-15T02:30:55Z 2018 Journal Article Zhou, L., Ding, L., Ma, M., & Tang, W. (2019). An accurate partially attracted firefly algorithm. Computing, 101(5), 477-493. doi:10.1007/s00607-018-0645-2 0010-485X https://hdl.handle.net/10356/139039 10.1007/s00607-018-0645-2 2-s2.0-85050256682 5 101 477 493 en Computing © 2018 Springer-Verlag GmbH Austria, part of Springer Nature. All rights reserved. |
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Engineering::Computer science and engineering Firefly Algorithm Partial Attraction Model Zhou, Lingyun Ding, Lixin Ma, Maode Tang, Wan An accurate partially attracted firefly algorithm |
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The firefly algorithm (FA) is a new and powerful algorithm for optimization. However, it has the disadvantages of high computational complexity and low convergence accuracy, especially when solving complex problems. In this paper, an accurate partially attracted firefly algorithm (PaFA) is proposed by adopting a partial attraction model and a fast attractiveness calculation strategy. The partial attraction model can preserve swarm diversity and make full use of individual information. The fast attractiveness calculation strategy ensures information sharing among the individuals and it also improves the convergence accuracy. The experimental results demonstrate the good performance of PaFA in terms of the solution accuracy compared with two state-of-the-art FA variants and two other bio-inspired algorithms. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Zhou, Lingyun Ding, Lixin Ma, Maode Tang, Wan |
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Article |
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Zhou, Lingyun Ding, Lixin Ma, Maode Tang, Wan |
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Zhou, Lingyun |
title |
An accurate partially attracted firefly algorithm |
title_short |
An accurate partially attracted firefly algorithm |
title_full |
An accurate partially attracted firefly algorithm |
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An accurate partially attracted firefly algorithm |
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An accurate partially attracted firefly algorithm |
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accurate partially attracted firefly algorithm |
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2020 |
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https://hdl.handle.net/10356/139039 |
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1681056452611932160 |