Research on floating point representation genetic algorithm based on wavelet threshold shrinkage denoising

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 mutation. It cannot avoid the noise to influence on the algorithm performance. This paper presents a floating point representation genetic algorithm based on wavelet threshold shrinkage denoising (FGAWSD). A filter was structured. Mutation operation was replaced with different thresholds denoising. The experiments were done. The result of the research and the experiments indicates that the method is reliable in theory, is feasible in technique. The precision of the optimal solution of problem can be enhanced with selecting proper threshold. The method is of high stability.