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Gravitational Search Algorithm: A State-of-the-Art Review

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Harmony Search and Nature Inspired Optimization Algorithms

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 741))

Abstract

Gravitational search algorithm (GSA) is a recent algorithm introduced in 2009 by Rashedi et al. It is a heuristic optimization algorithm based on Newton’s laws of motion and law of Gravitation. Till now, a lot of changes have been done in original GSA to improve its speed of convergence and its quality of solution; also this algorithm is still exploring in many fields. Therefore, this article is intended to provide the current state of algorithm, modifications, advantages, disadvantages, and its future possibilities of research.

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Acknowledgements

This research is supported by National Institute of Technology Uttarakhand and North-cap university (NCU) Gurgaon.

Author information

Authors and Affiliations

  1. Northcap University, Gurgaon, 122017, India

    Indu Bala

  2. National Institute of Technology Uttarakhand, Srinagar, 246174, India

    Anupam Yadav

Authors
  1. Indu Bala
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  2. Anupam Yadav
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Corresponding author

Correspondence to Indu Bala .

Editor information

Editors and Affiliations

  1. School of Engineering and Technology, BML Munjal University, Gurgaon, Haryana, India

    Neha Yadav

  2. Department of Sciences and Humanities, National Institute of Technology, Srinagar, Uttarakhand, India

    Anupam Yadav

  3. Department of Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

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

    Kusum Deep

  5. School of Civil, Environmental and Architectural Engineering, Korea University, Seoul, Korea (Republic of)

    Joong Hoon Kim

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Bala, I., Yadav, A. (2019). Gravitational Search Algorithm: A State-of-the-Art Review. In: Yadav, N., Yadav, A., Bansal, J., Deep, K., Kim, J. (eds) Harmony Search and Nature Inspired Optimization Algorithms. Advances in Intelligent Systems and Computing, vol 741. Springer, Singapore. https://doi.org/10.1007/978-981-13-0761-4_3

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