摘要
为处理系统评价中各评价指标的一致无量纲化问题,避开模糊综合评价方法中建立隶属度函数的困难,探讨了用模糊优先关系矩阵A的优度值作为各评价指标的一致化和无量纲化值的新途径。为充分利用A的一致性信息和提高A的优度值计算结果的可信程度,提出了A的最优模糊一致性判断矩阵、一致性指标函数和一致性指标临界值。研制了用加速遗传算法检验、修正A的一致性,并同时计算A各评价对象优度值的新的系统评价方法(AGA-FPRM)。理论和实例分析的初步结果表明,AGA-FPRM方法直观、实用,矩阵修正幅度较小,计算结果稳定、精度高,可在模糊层次分析法理论与实践中推广应用。
In order to make consistency and to eliminate dimensions of system evaluation indexes, and to avoid determining membership function in fuzzy comprhensive evaluation, a new approach is studied with which preference values of fuzzy preferential relation matrix A can be used as consistency and nondimension evaluation indexes. Optimal fuzzy consistency judgement matrix, consistency index function and consistency index critical value of matrix A are presented in order to make the most of consistency information of matrix A ,and to improve believable degree of computed preference values of matrix A. A new system evaluation method, named AGA-FPRM, is proposed to check and correct the consistency of matrix A and to compute preference values at the same time by using accelerating genetic algorithm improved by the authors. The results of theoretical analysis and case study show that AGA-FPRM is visual, practical, that correcting range of matrix A less, that its result is both stable and highly precise, and that it possesses important theoretical significance and broad application value in fuzzy analytic hierarchy process.
出处
《系统工程理论方法应用》
北大核心
2005年第4期364-368,共5页
Systems Engineering Theory·Methodology·Applications
基金
教育部优秀青年教师资助项目(教人司[2002]350)
安徽省优秀青年科技基金资助项目
安徽省自然科学基金资助项目(01045102)
四川大学高速水力学国家重点实验室开放基金资助项目(0201)
关键词
模糊优先关系矩阵
系统评价
遗传算法
层次分析法
fuzzy preferential relation matrix
system evaluation
genetic algorithm
analytic hierarchy process
