Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
An Introduction to Genetic Algorithms for Scientists and Engineers
An Introduction to Genetic Algorithms for Scientists and Engineers
Quality Engineering Using Robust Design
Quality Engineering Using Robust Design
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Electromagnetic Optimization by Genetic Algorithms
Electromagnetic Optimization by Genetic Algorithms
Adapting Operator Probabilities in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Practical Genetic Algorithms with CD-ROM
Practical Genetic Algorithms with CD-ROM
Antenna Theory: Analysis and Design
Antenna Theory: Analysis and Design
Combining mutation operators in evolutionary programming
IEEE Transactions on Evolutionary Computation
An orthogonal genetic algorithm with quantization for globalnumerical optimization
IEEE Transactions on Evolutionary Computation
Hybrid Taguchi-genetic algorithm for global numerical optimization
IEEE Transactions on Evolutionary Computation
| Hi-index | 0.00 |
In this paper, a hybrid Taguchi-genetic algorithm (HTGA) is used to optimize Yagi---Uda antennas. The method combines the traditional genetic algorithm, known to have a powerful global exploration capability, with the Taguchi method, which can exploit the optimum offspring and consequently, enhance the genetic algorithm. The aim is to devise antenna geometrical parameters that allow the antenna to simultaneously improve multiple performances such as gain, sidelobe level, and input impedance. Thus, not only will a new antenna configuration be found, but the demonstration of the ability of the HTGA method to design antenna structures with more than one goal is investigated as well.