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Mutation-Based Chaotic Gravitational Search Algorithm

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Proceedings of the Global AI Congress 2019

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1112))

Abstract

Gravitational search algorithm, a stochastic, nature-inspired algorithm, is designed on the basis of gravitational kinematics of physics. To promote an appropriate stability between exploration and exploitation and to diminish the weakness that was affecting the search to reach global optima, a new variant of GSA named as mutation-based chaotic gravitational search algorithm (MCGSA) is introduced in this work. This new variant of GSA consists of five mutation strategies. These five mutations are applied to the best solution in a successive manner. To justify the overall functioning of the proposed method, it has been evaluated on CEC2005 benchmark suit and has been compared with four other modified versions derived from original GSA, namely standard GSA (SGSA), chaotic-based GSA (CGSA), crossover-based GSA (CROGSA), and self-adaptive GSA (GGSA). The comprehensive result of MCGSA has outperformed other GSA variants.

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Authors and Affiliations

  1. Maulana Abul Kalam Azad University of Technology, Haringhata, Nadia, West Bengal, India

    Moujinjir Mukherjee, Suman Mitra & Sriyankar Acharyya

Authors
  1. Moujinjir Mukherjee
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  2. Suman Mitra
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  3. Sriyankar Acharyya
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Corresponding author

Correspondence to Suman Mitra .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

  2. Department of Computer Science and Engineering, Assam University, Silchar, Assam, India

    Somnath Mukhopadhyay

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Mukherjee, M., Mitra, S., Acharyya, S. (2020). Mutation-Based Chaotic Gravitational Search Algorithm. In: Mandal, J., Mukhopadhyay, S. (eds) Proceedings of the Global AI Congress 2019. Advances in Intelligent Systems and Computing, vol 1112. Springer, Singapore. https://doi.org/10.1007/978-981-15-2188-1_10

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