Document Type: Research Paper


1 Lahore School of Economics, Centre for Mathematics and Statistical Sciences, Lahore, Paksitan

2 Centre for Mathematics and Statistical Sciences, Lahore School of Economics, Lahore, 54000, Pakistan


In this article, we propose a method to deal with incomplete interval-valued
hesitant fuzzy preference relations. For this purpose, an additive
transitivity inspired technique for interval-valued hesitant fuzzy
preference relations is formulated which assists in estimating missing
preferences. First of all, we introduce a condition for decision makers
providing incomplete information. Decision makers expressing incomplete data
are expected to abide by the proposed condition. This ensures that the
estimated preferences are well-defined intervals which otherwise may not be
possible. Additionally, this condition eliminates the problem of outlying
estimated preferences. After resolving the issue of incompleteness, this
article proposes a ranking rule for reciprocal and non-reciprocal
interval-valued hesitant fuzzy preference relations.


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