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|Title:||An accurate partially attracted firefly algorithm||Authors:||Zhou, Lingyun
|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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