Group decision-making model with incomplete fuzzy preference relations based on additive consistency (original) (raw)
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Group decision making with incomplete fuzzy linguistic preference relations
International Journal of Intelligent Systems, 2009
The aim of this paper is to propose a procedure to estimate missing preference values when dealing with incomplete fuzzy linguistic preference relations assessed using a two-tuple fuzzy linguistic approach. This procedure attempts to estimate the missing information in an individual incomplete fuzzy linguistic preference relation using only the preference values provided by the respective expert. It is guided by the additive consistency property to maintain experts' consistency levels. Additionally, we present a selection process of alternatives in group decision making with incomplete fuzzy linguistic preference relations and analyze the use of our estimation procedure in the decision process. C
On Consensus in Group Decision Making Based on Fuzzy Preference Relations
Studies in Fuzziness and Soft Computing, 2011
In the process of decision making, the decision makers usually provide inconsistent fuzzy preference relations, and it is unreasonable to get the priority from an inconsistent preference relation. In this paper, we propose a method to derive the multiplicative consistent fuzzy preference relation from an inconsistent fuzzy preference relation. The fundamental characteristic of the method is that it can get a consistent fuzzy preference relation considering all the original preference values without translation. Then, we develop an algorithm to repair a fuzzy preference relation into the one with weak transitivity by using the original fuzzy preference relation and the constructed consistent one. After that, we propose an algorithm to help the decision makers reach an acceptable consensus in group decision making. It is worth pointing out that group fuzzy preference relation derived by using our method is also multiplicative consistent if all individual fuzzy preference relations are multiplicative consistent. Some examples are also given to illustrate our results.
Incomplete Hesitant Fuzzy Preference Relations in Group Decision Making
International Journal of Fuzzy Systems, 2016
In this article, incomplete hesitant fuzzy preference relations are under consideration. In order to estimate expressible missing preferences, a hesitant upper bound condition (hubc) is defined for decision makers presenting incomplete information. With the help of this condition, the estimated preference intensities lie inside the defined domain and thus are expressible. An algorithm is proposed to revise minimal possible preferences so that the resultant satisfies property (hubc). Moreover, ranking rule, HF-Borda count, for hesitant fuzzy preference relations is defined. This method dissolves possible ties among alternatives.
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Triangular fuzzy numbers are effective in modeling imprecise and uncertain information, and have been widely applied in decision making. This paper uses a cross-ratio-expressed triplet to characterize a positive triangular fuzzy number, and introduces notions of crossratio-expressed triangular fuzzy numbers (CRETFNs) and triangular fuzzy additive reciprocal preference relations (TFARPRs). We present transformation methods between TFARPRs and triangular fuzzy multiplicative reciprocal preference relations, and develop operational laws of CRETFNs, such as complement, addition, multiplication and power. A crossratio-expressed triangular fuzzy multiplication based transitivity equation is established to define multiplicative consistency of TFARPRs. The new consistency captures Tanino's multiplicative consistency among the cross-ratio-expressed modal values, and geometric consistency of the interval fuzzy preference relation constructed from lower and upper support values of cross-ratio-expressed triangular fuzzy judgments. Some desirable properties are furnished for multiplicatively consistent TFARPRs. We propose a cross-ratio-expressed triangular fuzzy weighted geometric operator to aggregate CRETFNs, and extend it to fuse TFARPRs. Score and uncertainty index functions are defined and employed to devise a novel comparison method for CRETFNs. A detailed procedure is put forward to solve group decision making problems with TFARPRs. Six numerical examples are provided to illustrate the validity and applicability of the proposed models.
New Fuzzy Preference Relations and its Application in Group Decision Making
akademik.unsri.ac.id
Abstract—Decision making preferences to certain criteria usually focus on positive degrees without considering the negative degrees. However, in real life situation, evaluation becomes more comprehensive if negative degrees are considered concurrently. Preference is expected to be more ...
International Journal of Information Technology & Decision Making, 2014
As we may have a set of possible values when comparing alternatives (or criteria), the hesitant fuzzy preference relation becomes a suitable and powerful technique to deal with this case. This paper mainly focuses on the consistency of the hesitant fuzzy preference relation. Before that, we explore some properties of the hesitant fuzzy preference relation and develop some new aggregation operators. Then we introduce the concepts of multiplicative consistency, perfect multiplicative consistency and acceptable multiplicative consistency for a hesitant fuzzy preference relation, based on which, two algorithms are given to improve the inconsistency level of a hesitant fuzzy preference relation. Furthermore, the consensus of group decision making is studied based on the hesitant fuzzy preference relations. Finally, several illustrative examples are given to demonstrate the practicality of our algorithms.
Mathematics, 2019
In this paper, a consensus-based method for multi-person decision making (MPDM) using product transitivity with incomplete fuzzy preference relations (IFPRs) is proposed. Additionally, an average aggregation operator has been used at the first level to estimate the missing preference values and construct the complete fuzzy preference relation (FPR). Then it is confirmed to be product consistent by using the transitive closure formula. Following this, weights of decision makers (DMs) are evaluated by merging consistency weights and predefined priority weights (if any). The consistency weights for the DMs are estimated through product consistency investigation of the information provided by each DM. The consensus process determines whether the selection procedure should be initiated or not. The hybrid comprises of a quitting process and feedback mechanism, and is used to enhance the consensus level amongst DMs in case of an inadequate state. The quitting process arises when some DMs d...
Development of group decision making model under fuzzy environment
2011
Multi criteria group decision making (MCGDM) methods are broadly used in the real-world decision circumstances for homogeneous groups. Some decision-makers’viewpoints at times are more important or reliable than others, or they may differ in terms of the decision-maker experience, education, expertise and other aspects. Thus, a heterogeneous group of decision makers with dissimilar members has to be composed in MCGDM. Multi-dimensional personnel evaluation is one of the most critical decisions to make in order to achieve the organization goals. In many situations, raters may decide on the basis of imprecise information coming from a variety of sources about ratee with respect to criteria. In fact, some criteria are completely quantifiable, some partially quantifiable, and others completely subjective; moreover crisp data is inappropriate to model real-world circumstances. Linguistic labels or fuzzy preferences are therefore, used to deal with uncertain and inaccurate factors involve...