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Improved PSO Algorithm with Harmony Search for Complicated Function Optimization Problems

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Advances in Neural Networks – ISNN 2012 (ISNN 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7367))

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Abstract

Improved particle swarm optimization algorithm with harmony search (IHPSO) is proposed in this paper. This algorithm takes particle swarm search direction estimation mechanism and harmony search (HS) approach to particle swarm optimization (PSO) algorithm, which increases the search capability of PSO algorithm considerably. The proposed algorithm initializes a new search with harmony pitch adjusting or random selection when PSO search direction is estimated incorrectly. This can provide further opportunities of finding better solutions for the particle swarm by guiding the entire particle swarm to promising new regions of the search space and accelerating the search. PSO, HPSO and IHPSO, as well as other advanced PSO procedures from the literature were compared on several benchmark test functions extensively. Statistical analyses of the experimental results indicate that the performance of IHPSO is better than the performance of PSO and HPSO.

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Yu, J., Guo, P. (2012). Improved PSO Algorithm with Harmony Search for Complicated Function Optimization Problems. In: Wang, J., Yen, G.G., Polycarpou, M.M. (eds) Advances in Neural Networks – ISNN 2012. ISNN 2012. Lecture Notes in Computer Science, vol 7367. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31346-2_70

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  • DOI: https://doi.org/10.1007/978-3-642-31346-2_70

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31345-5

  • Online ISBN: 978-3-642-31346-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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