关键词: 分组遗传算法, 智能化, 特征选择, 搜索空间

Abstract: Canonical genetic algorithm in the evolutionary process，fall into local convergence easy，premature convergence and low efficiency，to solve the problem，this paper presents a novel intelligentizing grouping genetic algorithm combining feature selection，intelligenting grouping genetic operation on genes in the evolution process using feature selection principle and grouping optimize idea，the fitness function at the introduction of individual feature and dynamic environmental fitness assessment model to build.This algorithm ensures the excellent genetic model of parent generation to the next generation and speeds up the algorithm convergence rate by the grouping genetic operation，grouping mutation operator expands the scope of the search，and make working out the local optimal solution.Application experimental results show algorithm has a strong immunity to the local optimal solution and the evolution algebra of searching the global optimal solution effectively less than canonical genetic algorithm，has high convergence precision and indicating the effectiveness of the proposed method.

Key words: grouping genetic algorithms, intelligentizing, feature selection, searching space