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Go to Editorial ManagerIn this article, a hybrid optimization method has been proposed consisting of Adaptive Genetic Algorithms (AGAs) and Constrained Nonlinear Programming (NLP) to solve the problems of performance optimization of circular array antenna consisting paraOel center feeding short dipoles elements with two complex nonlinear optimization problems. In the first problem. the hybrid optimization algorithm is used to reduce the value of sidelobe level in the circular array radiation pattern by finding the oPtlmal values of the excitation coefficients of each element in the clrcular array. In the second problem, a synthesis of circular array with different forms of the desired radiation pattern is considered. Several examples are considered here to verify the validlty of this method. Comparisons were made between the results of this method and the results obtained by {SGA) Standard Genetic Algorithm, and it is clearly shown that this method is more efficient and flexible in solving the problems of performance optimization of circular array antenna .
This paper describes the problem of minimizing-the sidelobe levels in the radiation pattern of antenna arrays by using the genetic algorithm. Two types of genetic algorithms representation are used here:., binaiy and continuous genetic algorithms depending on the nature of the problem at hand. Adaptive genetic algorithm wnich is a special type of genetic algorithm is used in this work. The obtained results explain the capability of this approach to obtain the desired sidelobe level.