Triple and quadruple comparison-based interactive differential evolution and differential evolution
Proceedings of the twelfth workshop on Foundations of genetic algorithms XII
Chaotic Evolution: fusion of chaotic ergodicity and evolutionary iteration for optimization
Natural Computing: an international journal
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We propose to apply n dimensional discrete Fourier transform (DFT) to a fitness landscape, search an elite individual using obtained principal frequency component and accelerate evolutionary computation (EC) search. a comparative evaluation with our previous works is conducted using eight benchmark functions. the evaluation shows that our proposed approach can obtain the accurate fitness landscape than that with 1 dimensional DFT, and EC acceleration performance can be improved significantly. However, it needs more computational time in the process of conducting n dimensional DFT than that in 1 dimension. We also investigate the computational complexity of the two approaches and some related issues.