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Expedited Artificial Bee Colony Algorithm

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Proceedings of the Third International Conference on Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 259))

Abstract

Artificial Bee Colony (ABC) is one of the latest and emerging swarm intelligence algorithms. Though, there are some areas where ABC works better than other optimization techniques but, the drawbacks like stucking at local optima and preferring exploration at the cost of exploitation, are also associated with it. This paper uses position update equation in ABC as in Gbest-guided ABC (GABC) and attempts to improve ABC algorithm by balancing its exploration and exploitation capabilities. The proposed algorithm is named as Expedited Artificial Bee Colony (EABC). We altered the onlooker bee phase of ABC by forcing the individual bee to take positive direction towards the random bee if this selected random bee has better fitness than the current bee and if it is not the case then the current bee will move in reverse direction. In this way, ABC colony members will not follow only global best bee but also a random bee which has better fitness than the current bee which is going to be modified. So the mentioned drawbacks of the ABC may be resolved. To analyze the performance of the proposed modification, 14 unbiased benchmark optimization functions have been considered and experimental results reflect its superiority over the Basic ABC and GABC.

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Authors and Affiliations

  1. ABV-Indian Institute of Information Technology and Management, Gwalior, India

    Shimpi Singh Jadon & Ritu Tiwari

  2. South Asian University, New Delhi, India

    Jagdish Chand Bansal

  3. Government Engineering College, Jhalawar, India

    Harish Sharma

Authors
  1. Shimpi Singh Jadon
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  2. Jagdish Chand Bansal
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  3. Ritu Tiwari
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  4. Harish Sharma
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Corresponding author

Correspondence to Shimpi Singh Jadon .

Editor information

Editors and Affiliations

  1. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Millie Pant

  2. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Kusum Deep

  3. Department of Mathematics and Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya Nagar

  4. Department of Applied Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

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Jadon, S.S., Bansal, J.C., Tiwari, R., Sharma, H. (2014). Expedited Artificial Bee Colony Algorithm. In: Pant, M., Deep, K., Nagar, A., Bansal, J. (eds) Proceedings of the Third International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 259. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1768-8_68

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  • DOI: https://doi.org/10.1007/978-81-322-1768-8_68

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-1767-1

  • Online ISBN: 978-81-322-1768-8

  • eBook Packages: EngineeringEngineering (R0)

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