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Computational Methods pp 1075–1080Cite as

A HERO EVOLUTIONARY ALGORITHM HYBRIDIZING FROM PSO AND GA

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Abstract

Both GA and PSO are typical evolution algorithm with their own advantages. In this paper, a new evolution algorithm is introduced based on GA and PSO. The total population are divided into several tribes, which one Hero individual and several common particles are included in each tribe. The movement velocity of each hero is calculated by global peak point and local best point among this tribe just like PSO. Other common particles will search neighbourhood of hero using recombination method of GA. Hero algorithm will converge fast and escape from local peak inheriting advantages of GA and PSO. These conclusions are proven from experiment of some familiar Benchmark functions.

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REFERENCES

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Author information

Authors and Affiliations

  1. College of Computer Science and Technology, Jilin University, Changchun, 130012, P.R. China

    D.W. Guo, C.G. Zhou & M. Liu

Authors
  1. D.W. Guo
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  2. C.G. Zhou
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  3. M. Liu
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Editor information

Editors and Affiliations

  1. National University of Singapore, Singapore

    G.R. LIU

  2. National University of Singapore, Singapore

    V.B.C. TAN

  3. Hunan University, P.R. China

    X. HAN

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© 2006 Springer

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Cite this paper

Guo, D., Zhou, C., Liu, M. (2006). A HERO EVOLUTIONARY ALGORITHM HYBRIDIZING FROM PSO AND GA. In: LIU, G., TAN, V., HAN, X. (eds) Computational Methods. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-3953-9_10

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  • DOI: https://doi.org/10.1007/978-1-4020-3953-9_10

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-3952-2

  • Online ISBN: 978-1-4020-3953-9

  • eBook Packages: EngineeringEngineering (R0)

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