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Floating point representation (FPR) is of the strongpoint of high precision and facilitating search on high-dimension space. It is superior to other representation in function optimization and restriction optimization. But, the noise was brought about in run environment of floating point representation genetic algorithm (FPRGA). This was often neglected by researchers. Simple FPRGA uses bounded random...
In research on genetic algorithm (GA), encoding is one of difficult problems. The past research indicated which float code (FC) could be super to other codes in function and restriction optimization. It was ignored by researchers how FC was denoised in running environment of GA for enhancing the performance of GA. In this paper, it was proved that odd-length and even-length of chromosome could all...
Encoding is one of difficult problem of research on genetic algorithm (GA). Float code (FC) is super to other codes in function and restriction optimization. But it was ignored by researchers how FC was denoised in running environment of GA for enhancing the performance of GA. In this paper, it was proved by the wavelet theory that odd-length and even-length of chromosome encoded could all mutate...
Since differential evolution (DE) proposed by researchers, it has been being the focus researched in evolutionary computation. There are better search performance, stronger robustness and higher perturbation property in DE. In improving the performance of algorithm and running quality, extending evolution algorithm application to engineering optimization, float code is superior to other codes. In...
Coding is an important and a difficult subject of research on genetic algorithm (GA). Float code (FC) is super to other codes in use. But, noise and its influence on GA performance were ignored by researches in genetic operation. Mutation played an important role of improving GA performance. This paper presents a float-coded genetic algorithm (FCGA) with wavelet denoising mutation. They are called...
Niche had better performance in increasing the population diversity of genetic algorithm (GA), in improving local researching performance of it. So far, research results of relating to niche GA were all on binary representation, there was almost no on float representation genetic algorithm (FRGA). But in improving the performance of GA and extending GApsilas application, float representation is superior...
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