Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/139039
Title: An accurate partially attracted firefly algorithm
Authors: Zhou, Lingyun
Ding, Lixin
Ma, Maode
Tang, Wan
Keywords: Engineering::Computer science and engineering
Issue Date: 2018
Source: 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
Journal: Computing
Abstract: 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.
URI: https://hdl.handle.net/10356/139039
ISSN: 0010-485X
DOI: 10.1007/s00607-018-0645-2
Rights: © 2018 Springer-Verlag GmbH Austria, part of Springer Nature. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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