Abstract: Coding issue is a difficult problem of Genetic Algorithm（GA） research. Floating Point Representation（FPR） is superior to other codes in function optimization and restriction optimization. FPR can improve local search performance of GA. Lately, the attention of researches is attracted to the noises generated by FPR in genetic environment and its influence on algorithm performance. But few research result is emerged on FPR denoising mutation based on multiwavelet thresholding. In this paper, the properties of multiwavelet and FPR noises are researched, the method of FPR denoising mutation is presented on multiwavelet thresholding, the experiments are carried out by the author. The experiment result is compared with other method. The results of the research and the experiments indicate which the method can raise the convergence precision and velocity of the algorithm, improve whole performance of the algorithm.

Key words: multiwavelet, threshold, Floating Point Representation（FPR）, denoising mutation, genetic algorithm

摘要： 编码问题是遗传算法研究的难点。浮点数编码在函数和约束优化中明显优于其他编码，并能提高算法的局部搜索能力。浮点数编码在遗传环境中产生的噪音和对算法性能的影响，正在被研究者所关注。但目前尚无基于多小波阈值实现浮点数编码消噪变异的研究成果出现。首先研究了多小波和浮点数编码噪音的性质，提出了一种基于多小波阈值的浮点数编码消噪变异方法，并与其他算法进行比较实验。研究和实验结果表明，这种方法可明显提高算法的收敛精度和速度，改善算法的整体性能。

关键词: 多小波, 阈值, 浮点数编码, 消噪变异, 遗传算法