FPRGA Based on Construction of Multiwavelets in Term of a Novel Transformation

Floating point representation (FPR) is of the advantage of higher precision and easy to search in high-dimension space. FPR is in evidence superior to other codes in fields of function optimization and restriction optimization. It was not known by researchers that noise was generated by FPR genetic algorithm (FPRGA) in operation environment and how it affected on the algorithm performance. It is an available approach of solving the problem that wavelet is used to FPRGA denoising mutation. Single wavelet is of lower generalization ability in FPRGA denoising mutation. It is of a limitation of improving performance of FPRGA. The paper presented a floating point representation genetic algorithm based on multiwavelets in terms of a novel transformation (FGAMW). It was proved that orthogonal multiwavelet is constructed by unitary transform. Orthogonal multiwavelet was used to denoising mutation in FPRGA. The experiments were done in it.