期刊
NEURAL COMPUTING & APPLICATIONS
卷 30, 期 12, 页码 3859-3868出版社
SPRINGER LONDON LTD
DOI: 10.1007/s00521-017-2971-2
关键词
Antenna arrays; Circular antenna arrays; Optimization methods; Symbiotic organisms search
资金
- Jordan University of Science and Technology, Irbid, Jordan
This paper investigates the design of concentric circular antenna arrays (CCAAs) with optimum side lobe level reduction using the Symbiotic Organisms Search (SOS) algorithm. Both thinned and full CCAAs are considered. SOS represents a rather new evolutionary algorithm for antenna array optimization. SOS is inspired by the symbiotic interaction strategies between different organisms in an ecosystem. SOS uses simple expressions to model the three common types of symbiotic relationships: mutualism, commensalism, and parasitism. These expressions are used to find the global minimum of the fitness function. Unlike other methods, SOS is free of tuning parameters, which makes it an attractive optimization method. The results obtained using SOS are compared to those obtained using several optimization methods, like Biogeography-Based Optimization (BBO), Teaching-Learning-Based Optimization (TLBO), and Evolutionary Programming (EP). It is shown that the SOS is a robust straightforward evolutionary algorithm that competes with other known methods.
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