Additive Consistency of Hesitant Fuzzy Linguistic Preference Relation With a New Expansion Principle for Hesitant Fuzzy Linguistic Term Sets

2019 ◽  
Vol 27 (4) ◽  
pp. 716-730 ◽  
Author(s):  
Peng Wu ◽  
Ligang Zhou ◽  
Huayou Chen ◽  
Zhifu Tao
Keyword(s):  
Preference Relation ◽  
Additive Consistency ◽  
Linguistic Term ◽  
Linguistic Preference Relation ◽  
Fuzzy Linguistic

scholarly journals Using the Fuzzy Linguistic Preference Relation Approach for Assessing the Importance of Risk Factors in a Software Development Project

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Shih-Tong Lu ◽  
Shih-Heng Yu ◽  
Dong-Shang Chang ◽  
Shih-Chang Su
Keyword(s):  
Risk Factors ◽  
Software Development ◽  
Preference Relation ◽  
Development Project ◽  
Software Development Project ◽  
Linguistic Preference Relation ◽  
System Risk ◽  
Risk Dimensions ◽  
Fuzzy Linguistic ◽  
Information Collecting

This study employs fuzzy linguistic preference relation (Fuzzy LinPreRa) approach to assess the relative degree of impact of risk factors in software development project for two expert groups working in technology enterprises and software development companies. For the identified risk dimensions, the results show the same rankings for these two groups. “Organization function risk” is considered the most important dimension influencing the software development project performance, with the others, in order, being “developing technology risk,” “resources integration risk,” “personnel system risk” and “system requirement risk.” The proposed approach not only facilitates the information collecting for making pairwise comparisons, but it also eliminates the inconsistencies in the collected information.

scholarly journals A NEW MODEL FOR FUZZY PERSONALIZED ROUTE PLANNING USING FUZZY LINGUISTIC PREFERENCE RELATION

2017 ◽  
Vol XLII-4/W4 ◽  
pp. 417-421 ◽  
Author(s):  
S. Nadi ◽  
A. H. Houshyaripour
Keyword(s):  
Preference Relation ◽  
Route Planning ◽  
New Model ◽  
Proposed Model ◽  
Linguistic Preference Relation ◽  
Fuzzy Ranking ◽  
Fuzzy Linguistic ◽  
Personalized Routing ◽  
Different Sources ◽  
Modelling Process

This paper proposes a new model for personalized route planning under uncertain condition. Personalized routing, involves different sources of uncertainty. These uncertainties can be raised from user’s ambiguity about their preferences, imprecise criteria values and modelling process. The proposed model uses Fuzzy Linguistic Preference Relation Analytical Hierarchical Process (FLPRAHP) to analyse user’s preferences under uncertainty. Routing is a multi-criteria task especially in transportation networks, where the users wish to optimize their routes based on different criteria. However, due to the lake of knowledge about the preferences of different users and uncertainties available in the criteria values, we propose a new personalized fuzzy routing method based on the fuzzy ranking using center of gravity. The model employed FLPRAHP method to aggregate uncertain criteria values regarding uncertain user’s preferences while improve consistency with least possible comparisons. An illustrative example presents the effectiveness and capability of the proposed model to calculate best personalize route under fuzziness and uncertainty.

scholarly journals A Method Adjusting Consistency and Consensus for Group Decision-Making Problems with Hesitant Fuzzy Linguistic Preference Relations Based on Discrete Fuzzy Numbers

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Meng Zhao ◽  
Ting Liu ◽  
Jia Su ◽  
Meng-Ying Liu
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Preference Relation ◽  
Feedback Mechanism ◽  
Preference Relations ◽  
Linguistic Preference Relation ◽  
Consensus Reaching Process ◽  
Fuzzy Linguistic

In each hesitant fuzzy linguistic preference relation, experts may express their opinions through comparison linguistic information combined with a discrete fuzzy number. In this paper, a hesitant fuzzy linguistic computational model based on discrete fuzzy numbers whose support is a subset of consecutive natural numbers is proposed, which enriches the flexibility of group decision-making. First, some main concepts related to discrete fuzzy numbers and an aggregation function of individual subjective linguistic preference relations are introduced. Then, a consistency measure is presented to check and improve the consistency in a given matrix. Further, in order to achieve the predefined degree of consensus and to arrive at the final result, a consensus-reaching process based on the interactive feedback mechanism is defined. Meanwhile, a revised formula is introduced to calculate the consistency and the degree of consensus in a preference relation matrix. Besides, an illustrative example and comparative analysis are conducted through the proposed calculation process and the optimization algorithm. Finally, the analysis on the threshold values is made to help the decision-maker determine critical consensus level. The proposed method can address both consistency and consensus, and the results confirmed the effectiveness of the proposed method and its potential use in the qualitative decision-making problems.

scholarly journals A NEW MULTI-CRITERIA EVALUATION MODEL BASED ON THE COMBINATION OF NON-ADDITIVE FUZZY AHP, CHOQUET INTEGRAL AND SUGENO λ-MEASURE

2017 ◽  
Vol XLII-4/W4 ◽  
pp. 423-428 ◽  
Author(s):  
S. Nadi ◽  
M. Samiei ◽  
H. R. Salari ◽  
N. Karami
Keyword(s):  
Choquet Integral ◽  
Fuzzy Ahp ◽  
Evaluation Model ◽  
Preference Relation ◽  
Fuzzy Preferences ◽  
Multi Criteria Evaluation ◽  
Proposed Model ◽  
Linguistic Preference Relation ◽  
Final Score ◽  
Fuzzy Linguistic

This paper proposes a new model for multi-criteria evaluation under uncertain condition. In this model we consider the interaction between criteria as one of the most challenging issues especially in the presence of uncertainty. In this case usual pairwise comparisons and weighted sum cannot be used to calculate the importance of criteria and to aggregate them. Our model is based on the combination of non-additive fuzzy linguistic preference relation AHP (FLPRAHP), Choquet integral and Sugeno λ-measure. The proposed model capture fuzzy preferences of users and fuzzy values of criteria and uses Sugeno λ -measure to determine the importance of criteria and their interaction. Then, integrating Choquet integral and FLPRAHP, all the interaction between criteria are taken in to account with least number of comparison and the final score for each alternative is determined. So we would model a comprehensive set of interactions between criteria that can lead us to more reliable result. An illustrative example presents the effectiveness and capability of the proposed model to evaluate different alternatives in a multi-criteria decision problem.

Sign in / Sign up

Export Citation Format

Share Document