Array pattern control in the complex plane optimised by a genetic algorithm

Array pattern synthesis in the complex plane optimised by a genetic algorithm

Electronics Letters ◽

10.1049/el:19961255 ◽

1996 ◽

Vol 32 (20) ◽

pp. 1843 ◽

Cited By ~ 15

Author(s):

R.J. Mitchell ◽

B. Chambers ◽

A.P. Anderson

Keyword(s):

Genetic Algorithm ◽

Complex Plane ◽

Pattern Synthesis ◽

Array Pattern

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Conformal array pattern synthesis on a curved surface with quadratic function using adaptive genetic algorithm

2013 Asia-Pacific Microwave Conference Proceedings (APMC) ◽

10.1109/apmc.2013.6695226 ◽

2013 ◽

Cited By ~ 3

Author(s):

Cheol-Min Seong ◽

Myung-seok Kang ◽

Cheol-Soo Lee ◽

Dong-Chul Park

Keyword(s):

Genetic Algorithm ◽

Quadratic Function ◽

Curved Surface ◽

Adaptive Genetic Algorithm ◽

Pattern Synthesis ◽

Conformal Array ◽

Array Pattern

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Innovative Genetic Algorithmic Approach to Select Potential Patches Enclosing Real and Complex Zeros of Nonlinear Equation

International Journal of Natural Computing Research ◽

10.4018/ijncr.2017070102 ◽

2017 ◽

Vol 6 (2) ◽

pp. 18-37 ◽

Cited By ~ 1

Author(s):

Vijaya Lakshmi V. Nadimpalli ◽

Rajeev Wankar ◽

Raghavendra Rao Chillarige

Keyword(s):

Genetic Algorithm ◽

Nonlinear Equation ◽

Complex Plane ◽

Search Space ◽

Regions Of Interest ◽

Real Numbers ◽

Algorithmic Approach ◽

Space Reduction ◽

Complex Zeros ◽

The Given

In this article, an innovative Genetic Algorithm is proposed to find potential patches enclosing roots of real valued function f:R→R. As roots of f can be real as well as complex, the function is reframed on to complex plane by writing it as f(z). Thus, the problem now is transformed to finding potential patches (rectangles in C) enclosing z such that f(z)=0, which is resolved into two components as real and imaginary parts. The proposed GA generates two random populations of real numbers for the real and imaginary parts in the given regions of interest and no other initial guesses are needed. This is the prominent advantage of the method in contrast to various other methods. Additionally, the proposed ‘Refinement technique' aids in the exhaustive coverage of potential patches enclosing roots and reinforces the selected potential rectangles to be narrow, resulting in significant search space reduction. The method works efficiently even when the roots are closely packed. A set of benchmark functions are presented and the results show the effectiveness and robustness of the new method.

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