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An Improved Artificial Bee Colony Algorithm Based on Gaussian Mutation and Chaos Disturbance

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Book cover Advances in Swarm Intelligence (ICSI 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7331))

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Abstract

Artificial Bee Colony (ABC) algorithm is a novel bio-inspired swarm intelligence approach which is competitive with other population-based algorithms and has the advantage of using fewer control parameters. However, basic ABC is easy to be prematurely convergent and be trapped into local optimum. In the later iteration, algorithm has low convergent speed and population diversity seriously decreases. In this paper, Gaussian mutation and chaos disturbance are introduced into ABC to overcome the shortcomings above. Applications of improved ABC algorithm on four benchmark optimization functions show marked improvement in performance over the basic ABC.

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Author information

Authors and Affiliations

  1. School of Information Science and Engineering, Shandong University, 250100, Jinan, China

    Xiaoya Cheng & Mingyan Jiang

Authors
  1. Xiaoya Cheng
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  2. Mingyan Jiang
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), Peking University, Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Shenzhen City Key Laboratory of Embedded System Design, College of Computer Science and Software Engineering, Shenzhen University, 518060, Shenzhen, China

    Zhen Ji

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© 2012 Springer-Verlag Berlin Heidelberg

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Cheng, X., Jiang, M. (2012). An Improved Artificial Bee Colony Algorithm Based on Gaussian Mutation and Chaos Disturbance. In: Tan, Y., Shi, Y., Ji, Z. (eds) Advances in Swarm Intelligence. ICSI 2012. Lecture Notes in Computer Science, vol 7331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30976-2_39

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  • DOI: https://doi.org/10.1007/978-3-642-30976-2_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30975-5

  • Online ISBN: 978-3-642-30976-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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