Abstract:
The problem of multi-person decision-making (MPDM) possesses a solution, the
quality of which may be influenced by the inclinations of experts. In certain essential
conditions, employing the fuzzy MPDM approach can yield more acceptable and
efficient outcomes for the selection of optimal alternatives. This study introduces a
consensus-based technique designed for the selection of alternatives within an
environment characterized by hesitant fuzzy preference relations (HFPRs). At the
initial stage, we introduced a scheme grounded in Lukasiewicz transitivity ( -
transitivity) to derive normalized hesitant fuzzy preference relations (NHFPRs).
Within this framework, a consensus-based model is formulated. Subsequently, a
transitive closure formula is defined to generate -consistent HFPRs, yielding
symmetrical matrices. Following this, a consistency analysis is conducted to assess
the consistency levels of information provided by decision-makers (DMs) and,
consequently, to allocate consistency weights to them. The ultimate priority weights
vector of DMs is computed by combining consistency weights with predefined
priority weights, if applicable. The consensus process determines whether data
aggregation and selection of the optimal alternative should proceed. An enhancement
mechanism is employed to refine the consensus measure among DMs, involving the
introduction of an identifier for identifying weak positions in cases of inadequate
consensus. The proposed approach is formulated using the Analytical Hierarchy
Process (AHP) framework criteria, and the decision matrix is created through the
utilization of consistent hesitant fuzzy preference relations (HFPRs
