Abstract: A new algorithm for getting core attributes is firstly given in this paper.Then simulated annealing genetic algorithm is improved by dynamic regulation of the nearest neighbor subset and used in minimal attribute reduction of decision table.This algorithm uses core attributes to optimize the initial population and adaptive crossover probability and mutation probability，restrains premature convergence effectively and enhancs the ability of search and efficiency.The experiment results demonstrate that the algorithm is efficient and feasible in minimal attribute reduction.

摘要： 首先给出求解决策表核属性集的算法，然后采用动态调节近邻子集的方法改进模拟退火遗传算法，应用于求解决策表的最小属性约简。该约简算法利用核属性集优化初始种群，并采用自适应方式动态选取交叉和变异概率，有效地抑制了早熟收敛现象，提高了算法在解空间中的探索能力和效率。实验结果显示该算法能有效求解决策表最小属性约简问题。