Abstract
In order to overcome the standard particle swarm optimization algorithm which is easily trapped in local minima and optimize the shortcoming of low precision, this paper proposed a way which can make multiple information exchange between particles come true: the multiple population co-evolution PSO algorithm. This paper proposes a multiple population co-evolutionary algorithm to achieve communication among populations, and then show the feasibility and effectiveness of this algorithm through experiments.
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**ao, X., Zhang, Q. (2014). The Multiple Population Co-evolution PSO Algorithm. In: Tan, Y., Shi, Y., Coello, C.A.C. (eds) Advances in Swarm Intelligence. ICSI 2014. Lecture Notes in Computer Science, vol 8795. Springer, Cham. https://doi.org/10.1007/978-3-319-11897-0_49
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DOI: https://doi.org/10.1007/978-3-319-11897-0_49
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11896-3
Online ISBN: 978-3-319-11897-0
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