An Improved Multi-Objective Genetic Algorithm for Large Planar Array Thinning.
- Resource Type
- Article
- Authors
- Cheng, You-Feng; Shao, Wei; Zhang, Sheng-Jun; Li, Ya-Peng
- Source
- IEEE Transactions on Magnetics. Mar2016, Vol. 52 Issue 3, p1-4. 4p.
- Subject
- *GENETIC algorithms
*FAST Fourier transforms
*ITERATIVE methods (Mathematics)
*STOCHASTIC convergence
*MATHEMATICAL optimization
- Language
- ISSN
- 0018-9464
In this paper, a novel hybrid multi-objective optimization algorithm based on the nondominated sorting genetic algorithm II for large array thinning is presented. The iterative fast Fourier transform (IFFT) technique with a judge factor is introduced into the optimizer to accelerate the convergence. The global characteristics of a genetic algorithm show its optimization capability in the early phase of the optimization process and the powerful local search ability of IFFT works in the late phase. Thus, this proposed algorithm can not only effectively avoid being trapped into the local optimum but also possess a fast convergence for large array thinning. Several representative examples of large planar thinned arrays validate the good performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]