Additive consistency analysis and improvement for hesitant fuzzy preference relations
作者： Zhen Zhang , Xinyue Kou , Qingxing Dong
DOI: 10.1016/J.ESWA.2018.01.016
关键词:
摘要: Abstract Hesitant fuzzy preference relation (HFPR) is an effective tool to elicit decision makers’ hesitant information over alternatives, and consistency analysis of great importance for HFPR since inconsistent judgments may result in unreasonable results. In this paper, the best additive index, worst index average are defined measure level HFPR. To improve HFPR, some mixed 0–1 linear programming models which aim minimize overall adjustment amount number elements that need be adjusted established. Moreover, proposed extended impute missing incomplete HFPRs. Some numerical examples presented show characteristics models. The results demonstrate can effectively.
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