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Spider Monkey Optimization Algorithm with Enhanced Learning

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Advances in Computing and Data Sciences (ICACDS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 906))

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Abstract

Spider Monkey Optimisation (SMO) is a new addition within the arena of nature-inspired algorithms. It is a recent Swarm Intelligence (SI) based algorithm, that models the food foraging behavior of a group of spider monkeys that mimic the Fission-Fusion Social System (FFSS) behavior. The SMO has been proven to be competitory and it balances the capabilities; exploitation and exploration efficiently. This article presents a significant variant of SMO, namely Spider Monkey Optimization with Enhanced Learning (SMOEL). In the proposed strategy, to increase the exploitation capability of SMO, an enhanced learning mechanism is introduced in the local leader stage that is based on the fitness of the solution. Reliability and accuracy of the intended algorithm are tested over 14 benchmarks functions and the comparison showed against various state of art algorithms available in the literature. The obtained outcomes prove the superiority of the intended algorithm.

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Authors and Affiliations

  1. Rajasthan Technical University, Kota, India

    Bhagwanti, Harish Sharma & Nirmala Sharma

Authors
  1. Bhagwanti
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  2. Harish Sharma
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  3. Nirmala Sharma
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Corresponding author

Correspondence to Bhagwanti .

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Editors and Affiliations

  1. University of KwaZulu-Natal, Durban, South Africa

    Mayank Singh

  2. Jaypee University of Information Technology, Solan, India

    P. K. Gupta

  3. Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, India

    Vipin Tyagi

  4. Institute of Information Theory and Automation, Prague 8, Czech Republic

    Jan Flusser

  5. University of Ottawa, Ottawa, Canada

    Tuncer Ören

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Bhagwanti, Sharma, H., Sharma, N. (2018). Spider Monkey Optimization Algorithm with Enhanced Learning. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2018. Communications in Computer and Information Science, vol 906. Springer, Singapore. https://doi.org/10.1007/978-981-13-1813-9_39

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  • DOI: https://doi.org/10.1007/978-981-13-1813-9_39

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1812-2

  • Online ISBN: 978-981-13-1813-9

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