The hesitant fuzzy preference relation (HFPR) and the hesitant multiplicative preference relation (HMPR) are emerging techniques in decision-making research field. Clearly, an intuitionistic idea to improve the above ...
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The hesitant fuzzy preference relation (HFPR) and the hesitant multiplicative preference relation (HMPR) are emerging techniques in decision-making research field. Clearly, an intuitionistic idea to improve the above preference relations is to synthesize the HFPR and the HMPR, which is also a primary contribution of this paper. Based on which, we propose the generalized HMPR (GHMPR) with full desired properties using transformation formulas that combine HFPR with HMPR and convert the HMPR into the GHMPR. Then, the GHMPR not only considers different risk appetites of a decision maker, but also preserves the advantages of both. Moreover, we design the corresponding consistency check algorithms, weight calculation methods and convergence algorithms for the GHMPR. Based on these new methods, we further propose a qualitative decision-making method under the GHMPR environment named as the analytic risk-network process (ARNP). Saaty's well-known analytic network process case is then utilized as an illustrated example to verify the feasibility of the proposed methods via comparisons. The simulation results show our proposed methods are effective and useful. (c) 2020 Elsevier Inc. All rights reserved.
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