动态三角模糊数互反判断矩阵一致性及修正

为了克服传统层次分析法中无法表现判断模糊性和系统时变性的缺点，提出了基于遗传算法的动态三角模糊数互反判断矩阵一致性检验、矩阵元素修正和权值排序的方法。将判断矩阵的一致性检验、矩阵元素修正和权值排序作为一个整体处理。采用小生境遗传算法优化求解建立的一致性指标系数非线性函数，可在对初始判断矩阵做最小程度修正的基础上使修正后的判断矩阵满足一致性要求，给出权值排序结果。分析了算法的复杂性和稳定性，并通过算例对比验证了方法的有效性。理论分析和算例对比表明，算法可充分利用初始判断矩阵信息，满足离线评估要求，在权值排序方面表现出稳定性。在有效解决评估系统模糊性和时变性方面具有意义。

Consistency and Correction of Dynamic Triangular Fuzzy Number Reciprocal Judgment Matrix

In order to overcome the disadvantages of the traditional hierarchical analysis method which can’t denote fuzziness and time-varying system,a niche genetic algorithm was used to examine the consistency of the dynamic triangular fuzzy number reciprocal judgment matrix,correct its matrix elements and order the weights.The method takes the consistency examination,matrix correction and weights ordering as an integral process.The genetic algorithm was adopted to optimize the nonlinear function of consistency index coefficient.The algorithm can make the corrected judgment matrixes have smaller consistency index coefficients on the basis of correcting the initial judgment matrixes to the smallest extend.The complexity and stability of the algorithm were analyzed,and its effectiveness was also proved by an example comparison.The theoretical analysis and example comparison show that the algorithm can take advantage of the initial judgment matrix information and meet the requirements of off-line assessment.And it has the stability in weights ordering.It is meaningful in overcoming the fuzziness and time-varying features of evaluation systems.