Abstract
In this paper, an improved particle swarm optimization algorithm is presented based on the local stable mechanism. The novelty of this kind of particle swarm optimization algorithm is that a certain part of the population stays at a stable level, while the rest part of the population uses the advantages of harmony search. The performance of this algorithm shows that this algorithm can effectively avoid the premature convergence problem. Moreover, this algorithm improves the ability of searching an optimum solution and increases the convergent speed.
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Wei, B., Li, Y., Shen, D., Yu, F., Xu, X. (2012). Local Stable Mechanism for Particle Swarm Optimization Algorithm. In: Liu, C., Wang, L., Yang, A. (eds) Information Computing and Applications. ICICA 2012. Communications in Computer and Information Science, vol 308. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34041-3_65
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DOI: https://doi.org/10.1007/978-3-642-34041-3_65
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34040-6
Online ISBN: 978-3-642-34041-3
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