Publication: Stochastic leader gravitational search algorithm for enhanced adaptive beamforming technique
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Date
2015
Authors
Darzi S.
Islam M.T.
Tiong S.K.
Kibria S.
Singh M.
Journal Title
Journal ISSN
Volume Title
Publisher
Public Library of Science
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 SLGSA is applied to minimum variance distortionless response (MVDR) beamforming technique to ensure compatibility with real world optimization problems. The proposed algorithmdemonstrates 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. � 2015 Darzi et al.
Description
controlled clinical trial; human; leadership; randomization; randomized controlled trial; stochastic model; algorithm; microwave radiation; procedures; search engine; theoretical model; wireless communication; Algorithms; Microwaves; Models, Theoretical; Random Allocation; Search Engine; Wireless Technology