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      Stochastic Leader Gravitational Search Algorithm for Enhanced Adaptive Beamforming Technique

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          Abstract

          In this paper, stochastic leader gravitational search algorithm (SL-GSA) based on randomized k is proposed. Standard GSA (SGSA) utilizes the best agents without any randomization, thus it is more prone to converge at suboptimal results. Initially, the new approach randomly choses k agents from the set of all agents to improve the global search ability. Gradually, the set of agents is reduced by eliminating the agents with the poorest performances to allow rapid convergence. The performance of the SL-GSA was analyzed for six well-known benchmark functions, and the results are compared with SGSA and some of its variants. Furthermore, the SL-GSA is applied to minimum variance distortionless response (MVDR) beamforming technique to ensure compatibility with real world optimization problems. The proposed algorithm demonstrates superior convergence rate and quality of solution for both real world problems and benchmark functions compared to original algorithm and other recent variants of SGSA.

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          Author and article information

          Contributors
          Role: Editor
          Journal
          PLoS One
          PLoS ONE
          plos
          plosone
          PLoS ONE
          Public Library of Science (San Francisco, CA USA )
          1932-6203
          9 November 2015
          2015
          : 10
          : 11
          Affiliations
          [1 ]Center for Space Science (ANGKASA), Universiti Kebangsaan Malaysia, Selangor, Malaysia
          [2 ]Department of Electrical, Electronic & Systems Engineering, Universiti Kebangsaan Malaysia, Selangor, Malaysia
          [3 ]Center of System and Machine Intelligence, College of Engineering, Universiti Tenaga Nasional, Selangor, Malaysia
          Beihang University, CHINA
          Author notes

          Competing Interests: The authors have declared that no competing interests exist.

          Conceived and designed the experiments: SD SKT. Performed the experiments: MTI. Analyzed the data: SD SK. Contributed reagents/materials/analysis tools: SD MS. Wrote the paper: SD.

          Article
          PONE-D-15-10080
          10.1371/journal.pone.0140526
          4638346
          26552032

          This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

          Counts
          Figures: 10, Tables: 10, Pages: 20
          Product
          Funding
          This work was supported by University Research Grant with project code DIP-2014-029. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
          Categories
          Research Article
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          All relevant data are within the paper.

          Uncategorized

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