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Adaptive switching gravitational search algorithm: an attempt to improve diversity of gravitational search algorithm through its iteration strategy

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Abstract

An adaptive gravitational search algorithm (GSA) that switches between synchronous and asynchronous update is presented in this work. The proposed adaptive switching synchronous–asynchronous GSA (ASw-GSA) improves GSA through manipulation of its iteration strategy. The iteration strategy is switched from synchronous to asynchronous update and vice versa. The switching is conducted so that the population is adaptively switched between convergence and divergence. Synchronous update allows convergence, while switching to asynchronous update causes disruption to the population’s convergence. The ASw-GSA agents switch their iteration strategy when the best found solution is not improved after a period of time. The period is based on a switching threshold. The threshold determines how soon is the switching, and also the frequency of switching in ASw-GSA. ASw-GSA has been comprehensively evaluated based on CEC2014’s benchmark functions. The effect of the switching threshold has been studied and it is found that, in comparison with multiple and early switches, one-time switching towards the end of the search is better and substantially enhances the performance of ASw-GSA. The proposed ASw-GSA is also compared to original GSA, particle swarm optimization (PSO), genetic algorithm (GA), bat-inspired algorithm (BA) and grey wolf optimizer (GWO). The statistical analysis results show that ASw-GSA performs significantly better than GA and BA and as well as PSO, the original GSA and GWO.12

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Acknowledgements

This research is funded by the Ministry of Higher Education, Malaysia, under the Fundamental Research Grant Scheme (\(\text {FRGS/1/2015/ICT02/MMU/03/1}\)), which is awarded to Multimedia University and the University of Malaya’s Postgraduate Research Grant (PG097-2013A). We are grateful to Dr Sophan Wahyudi Nawawi of Universiti Teknologi Malaysia for his input and support. The authors would also like to acknowledge the anonymous reviewers for their valuable comments and insights.

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Authors and Affiliations

  1. Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Nor Azlina Ab Aziz & Marizan Mubin

  2. Faculty of Engineering and Technology, Multimedia University, 75450, Melaka, Malaysia

    Nor Azlina Ab Aziz

  3. Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, 26600, Pekan, Pahang, Malaysia

    Zuwairie Ibrahim

  4. Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia

    Shahdan Sudin

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  1. Nor Azlina Ab Aziz
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Correspondence to Nor Azlina Ab Aziz or Marizan Mubin.

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Ab Aziz, N.A., Ibrahim, Z., Mubin, M. et al. Adaptive switching gravitational search algorithm: an attempt to improve diversity of gravitational search algorithm through its iteration strategy. Sādhanā 42, 1103–1121 (2017). https://doi.org/10.1007/s12046-017-0674-0

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