Investigation of fixed and variable mutation rate performances in real coded Genetic Algorithm for uniform circular antenna array pattern synthesis problem

2010 ◽  
Author(s):  
Fatih Yaman ◽  
Asim Egemen Yilmaz
Keyword(s):  
Genetic Algorithm ◽  
Antenna Array ◽  
Mutation Rate ◽  
Synthesis Problem ◽  
Pattern Synthesis ◽  
Array Pattern ◽  
Real Coded Genetic Algorithm ◽  
Circular Antenna Array

scholarly journals Impacts of Genetic Algorithm Parameters on the Solution Performance for the Uniform Circular Antenna Array Pattern Synthesis Problem

2010 ◽  
Vol 8 (03) ◽  
Author(s):  
F. Yaman ◽  
A. E. Ylmaz
Keyword(s):  
Genetic Algorithm ◽  
Antenna Array ◽  
Mutation Rate ◽  
Synthesis Problem ◽  
Pattern Synthesis ◽  
Array Pattern ◽  
Real Coded Genetic Algorithm ◽  
Random Position ◽  
Random Crossover ◽  
Circular Antenna Array

In this paper, the uniform circular antenna array pattern synthesis problem is solved by means of the real coded genetic algorithm (GA). At the same time, the impacts of the mutation rate and the crossover position on the GAperformance are also investigated. For this purpose, a circular antenna array with uniformly spaced isotropic elements having identical excitation amplitudes is used as a model. Unlike the conventional GA (with fixed mutation rate and random crossover positions), typical GA implementations with variable mutation rate and restricted crossover position are considered for performance improvement. In conclusion, for the specific problem, decreasing mutation rate with negative derivative is observed to be outperforming the implementations with different mutation rate behaviors. Moreover, regarding the crossover technique, it is observed that imposing some restrictions on the crossover positions (rather than fully random position selection) yields better solutions.

scholarly journals Circular Antenna Array Synthesis Using Multiverse Optimizer

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Ahmet Emre Taser ◽  
Kerim Guney ◽  
Erhan Kurt
Keyword(s):  
Antenna Array ◽  
Antenna Arrays ◽  
Mathematical Problem ◽  
Synthesis Process ◽  
Pattern Synthesis ◽  
White Hole ◽  
Array Pattern ◽  
Nature Inspired Algorithm ◽  
Antenna Array Synthesis ◽  
Circular Antenna Array

Antenna array synthesis is one of the most popular topics in the electromagnetic field. Since achieving a desired antenna radiation pattern is a mathematical problem, in the literature, there are various optimization algorithms applied to the synthesis process of different kinds of antenna arrays. In this study, Multiverse Optimizer (MVO) and modified MVO (MMVO) are used to perform circular antenna array (CAA) synthesis. During the exploration, exploitation, and local search phases of calculation, MVO uses three concepts in cosmology; white hole, black hole, and wormhole. Convergence capability of this nature-inspired algorithm is employed for finding optimum amplitude and position values of CAA elements in order to achieve an array pattern with low maximum sidelobe level (MSL) and minimum circumference. The performance of MVO and MMVO was tested on five design examples of pattern synthesis, and the obtained results were compared with ten different algorithms. The simulation results show that MVO and MMVO provide low MSLs with small circumferences.

Application of the Unit Circle Representation to Pattern Synthesis of Nonuniformly Spaced and Nonuniformly Excited Arrays based on the Teaching Learning Based Optimization

2019 ◽  
Vol 4 (1) ◽  
pp. 8-17
Author(s):  
Abdelmadjid RECIOUI
Keyword(s):  
Unit Circle ◽  
Antenna Array ◽  
Communication Systems ◽  
Sidelobe Level ◽  
Pattern Synthesis ◽  
Linear Arrays ◽  
Array Pattern ◽  
Teaching Learning Based Optimization ◽  
Null Placement ◽  
Teaching Learning

Pattern synthesis of Antenna array has gained much attention over the last years as they constitute an important role in the modern communication systems. Unit circle-based techniques such as Schelkunoff null placement method have proved their effectiveness to synthesize uniformly spaced linear arrays. Nonuniformly spaced antenna array pattern synthesis has been investigated and interesting results have been obtained. In this work, the unit circle representation approach is applied to synthesize nonuniformly spaced and nonuniformly excited linear arrays. The objective is to accurately place nulls in the desired directions while achieving the least possible sidelobe level. The problem is cast as an optimization problem that is solved using the Teaching Learning Based Optimization (TLBO). Examples are dealt with to prove the design approach effectiveness and flexibility for modern communication system applications.

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