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Social Evolution: An Evolutionary Algorithm Inspired by Human Interactions

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Proceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 2012

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 236))

Abstract

Inherent intelligent characteristics of humans, such as human interactions and information exchanges enable them to evolve more rapidly than any other species on the earth. Human interactions are generally selective and are free to explore randomly based on the individual bias. When the interactions are indecisive, individuals consult for second opinion to further evaluate the indecisive interaction before adopting the change to emerge and evolve. Inspired by such human properties, in this paper a novel social evolution (SE) algorithm is proposed and tested on four numerical test functions to ascertain the performance by comparing the results with the state-of-the-art soft computing techniques on standard performance metrics. The results indicate that, the performance of SE algorithm is better than or quite comparable to the state-of-the-art nature inspired algorithms.

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Acknowledgments

Authors gratefully acknowledge the inspiration and guidance of the Most Revered Prof. P. S. Satsangi, the Chairman, Advisory Committee on Education, Dayalbagh, Agra, India.

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Authors and Affiliations

  1. Dayalbagh Educational Institute, Dayalbagh, Agra, India

    R. S. Pavithr &  Gursaran

Authors
  1. R. S. Pavithr
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  2. Gursaran
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Corresponding author

Correspondence to R. S. Pavithr .

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Editors and Affiliations

  1. Institute of Engineering and Technology, JK Lakshmipat University, Jaipur, Rajasthan, India

    B. V. Babu

  2. Department of Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya Nagar

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

    Kusum Deep

  4. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, India

    Millie Pant

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

    Jagdish Chand Bansal

  6. Institute of Engineering and Technology, JK Lakshmipat University, Jaipur, Rajasthan, India

    Kanad Ray

  7. Institute of Engineering and Technology, JK Lakshmipat University, Jaipur, Rajasthan, India

    Umesh Gupta

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Pavithr, R.S., Gursaran (2014). Social Evolution: An Evolutionary Algorithm Inspired by Human Interactions. In: Babu, B., et al. Proceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 2012. Advances in Intelligent Systems and Computing, vol 236. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1602-5_153

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  • DOI: https://doi.org/10.1007/978-81-322-1602-5_153

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-1601-8

  • Online ISBN: 978-81-322-1602-5

  • eBook Packages: EngineeringEngineering (R0)

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