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Sensitivity Analysis For Hierarchical Decision Models, Hongyi Chen

Dissertations and Theses

In this dissertation, a comprehensive algorithm is developed to analyze the sensitivity of hierarchical decision models (HDM), which include the well-known analytic hierarchy process (AHP) and its variants, to single and multiple changes in the local contribution matrices at any level of the decision hierarchy. The algorithm is applicable to all HDM that use an additive function to derive the overall contribution vector. It is independent of pairwise comparison scales, judgment quantification techniques and group opinion combining methods. The direct impact of changes to a local contribution value on decision alternatives' overall contributions, allowable range/region of perturbations, contribution tolerance, operating …