【摘要】 采用层次分析法对顾客需求重要性进行排序时存在的两个问题:判断矩阵构造的主观性以及无法对权重相近的顾客需求进行精确排序。针对这两个问题,对传统的层次分析法进行改进,把判断矩阵的两两比较数值视为随机变量,采用有三点估计值的三角分布来确定,提出基于Monte Carlo-AHP方法的顾客需求重要性排序方法。最后通过一个案例进行对比分析,结果表明该方法是合理可行的,降低了主观判断的影响,提高了对顾客需求重要性进行精确排序的能力。更多还原

【Abstract】 There are two problems existed in ranking the importance weight of customer requirements based on traditional Analytic Hierarchical Process(AHP).The first one is the subjective assessments existed in the paired matrix,the second is the absence of the probability explanations of prioritizing the customer requirements in proximity which tend to confuse decision-makers.Therefore,in order to precisely identify the priorities of the adjacent customer requirements in final ordering,the pairwise values of every paired matrix were viewed as random variables and estimated by the triangular distribution,and a method in ranking the importance weight of customer requirements based on Monte Carlo-AHP was discussed.The results from the contrastive analysis of the example show that this logical and feasible method is an effective approach to reduce the subjectivity in building the paired matrixes and to enhance the ability of clearly prioritizing the adjacent customer requirements.更多还原