摘要
A min-max optimization method is proposed as a new approach to deal with the weight determination problem in the context of the analytic hierarchy process. The priority is obtained through minimizing the maximal absolute difference between the weight vector obtained from each column and the ideal weight vector. By transformation, the. constrained min- max optimization problem is converted to a linear programming problem, which can be solved using either the simplex method or the interior method. The Karush-Kuhn- Tucker condition is also analytically provided. These control thresholds provide a straightforward indication of inconsistency of the pairwise comparison matrix. Numerical computations for several case studies are conducted to compare the performance of the proposed method with three existing methods. This observation illustrates that the min-max method controls maximum deviation and gives more weight to non- dominate factors.
提出了层次分析法中一种用于确定权重的最小-最大优化方法. 其思路为通过最小化由两两比较矩阵中每列所得到的优先权和理想的权重向量之间的最大绝对差异来实现权重确定. 通过适当的变换,问题转化为可以采用单纯形或内点法求解的线性优化问题. 推导建立了解析的 Karush-Kuhn-Tucker 条件. 所建立的临界阀值提供了关于两两比较矩阵不一致特性的一种直接的表征. 给出了几种实例的数值算法,并比较了所提方法和3 种现有的权重确定方法的性能,观察结果发现最小-最大优化方法对于非主导因素有较多考虑.
基金
The US National Science Foundation (No. CMMI-0408390,CMMI-0644552,BCS-0527508)
the National Natural Science Foundation of China (No. 51010044,U1134206)
the Fok YingTong Education Foundation (No. 114024)
the Natural Science Foundation of Jiangsu Province (No. BK2009015)
the Postdoctoral Science Foundation of Jiangsu Province (No. 0901005C)
