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Strategic experts’ weight manipulation in 2-rank consensus reaching in group decision making

Published: 15 April 2023 Publication History

Highlights

We study the strategic experts’ weight manipulation in 2-rank consensus reaching in GDM.
We construct the 2-rank consensus level range model.
We construct the strategic experts’ weight manipulation model.
We design four simulation experiments to provide the comparative analysis.

Abstract

In group decision-making (GDM) problems, decision makers may prefer to divide the alternatives into two preference-ordered categories, which is called a 2-rank GDM problem. In the process of 2-rank GDM, consensus is of great significance for the aggregation of individual opinions, in which the experts’ weight plays a key role in the consensus level among experts, and different expert weights may lead to different 2-rank consensus results. Thus, a coordinator may strategically set experts’ weight to attain the desired consensus level, which we call strategic experts’ weight manipulation in 2-rank consensus reaching in GDM. In this study, first, we provided the concept of 2-rank consensus level range, and then we constructed a few mixed 0–1 linear programming models to compute the strategic experts’ weights to obtain the coordinator’s desired 2-rank consensus level, and the property is provided. Finally, we conducted a numerical example and a few simulation experiments to validate the effectiveness of our proposed models, and to show the effect of the number of experts and alternatives, respectively, on the process of strategic experts’ weight manipulation in 2-rank consensus reaching in GDM.

References

[1]
S. Aramesh, S.M. Mousavi, V. Mohagheghi, E.K. Zavadskas, J. Antucheviciene, A soft computing approach based on critical chain for project planning and control in real-world applications with interval data, Applied Soft Computing 98 (2021),.
[2]
M. Baucells, R.K. Sarin, Group decisions with multiple criteria, Management Science 49 (8) (2003) 1105–1118,.
[3]
D. Ben-Arieh, T. Easton, Multi-criteria group consensus under linear cost opinion elasticity, Decision Support Systems 43 (2007) 713–721,.
[4]
D. Ben-Arieh, T. Easton, B. Evans, Minimum cost consensus with quadratic cost functions, IEEE Transactions on Systems, Man, Cybernetics-Part A: Systems and Humans 39 (2009) 210–217,.
[5]
F.J. Cabrerizo, E. Herrera-Viedma, W. Pedrycz, A method based on PSO and granular computing of linguistic information to solve group decision making problems defined in heterogeneous contexts, European Journal of Operational Research 230 (3) (2013) 624–633,.
[6]
X. Chao, G. Kou, Y. Peng, E. Herrera-Viedma, Large-scale group decision-making with non-cooperative behaviors and heterogeneous preferences: An application in financial inclusion, European Journal of Operational Research 288 (1) (2021) 271–293,.
[7]
X. Chen, H.J. Zhang, Y.C. Dong, The fusion process with heterogeneous preference structures in group decision making, Information Fusion 24 (2015) 72–83,.
[8]
R.M. Cooke, Experts in uncertainty, Oxford University Press, Oxford, UK, 1991.
[9]
R.M. Cooke, L.L.H.J. Goossens, TU Delft expert judgment data base, Reliability Engineering & System Safety 93 (5) (2008) 657–674,.
[10]
J.E. Dannals, E.S. Reit, D.T. Miller, From whom do we learn group norms? Low-ranking group members are perceived as the best sources, Organizational Behavior and Human Decision Processes 161 (2020) 213–227,.
[11]
Y.C. Dong, H.J. Zhang, E. Herrera-Viedma, Integrating experts' weights generated dynamically into the consensus reaching process and its applications in managing non-cooperative behaviors, Decision Support Systems 84 (2016) 1–15,.
[12]
Y.C. Dong, Y.T. Liu, H.M. Liang, F. Chiclana, E. Herrera-Viedma, Strategic weight manipulation in multiple attribute decision making, Omega 75 (3) (2018) 154–164,.
[13]
Y.C. Dong, Y. Li, Y. He, X. Chen, Preference–approval structures in group decision making: Axiomatic distance and aggregation, Decision Analysis 18 (4) (2021) 273–295,.
[14]
Y.C. Dong, Q.B. Zha, H.J. Zhang, F. Herrera, Consensus reaching and strategic manipulation in group decision making with trust relationships, IEEE Transactions on Systems, Man, and Cybernetics: Systems 51 (10) (2021) 6304–6318,.
[15]
M. Fedrizzi, J. Kacprzyk, S. Zadrozny, An interactive multi-user decision support system for consensus reaching processes using fuzzy logic with linguistic quantifiers, Decision Support Systems 4 (1988) 313–327,.
[16]
Z.W. Gong, H.H. Zhang, J. Forrest, L.S. Li, X.X. Xu, Two consensus models based on the minimum cost and maximum return regarding either all individuals or one individual, European Journal of Operational Research 240 (1) (2015) 183–192,.
[17]
E. Herrera-Viedma, F. Herrera, F. Chiclana, A consensus model for multiperson decision making with different preference structures, IEEE Transactions on Systems, Man, and Cybernetics 32 (3) (2002) 394–402,.
[18]
D.S. Hochbaum, A. Levin, Methodologies and algorithms for group- rankings decision, Management Science 52 (9) (2016) 1394–1408,.
[19]
A. Ishizaka, P. Nemery, Multi-criteria decision analysis: Methods and software, John Wiley & Sons, 2013.
[20]
J. Kacprzyk, M. Fedrizzi, A ‘soft’ measure of consensus in the setting of partial (fuzzy) preferences, European Journal of Operational Research 34 (3) (1988) 316–325,.
[21]
J. Kacprzyk, M. Fedrizzi, H. Nurmi, Group decision making and consensus under fuzzy preferences and fuzzy majority, Fuzzy Sets and Systems 49 (1) (1992) 21–31,.
[22]
J. Kacprzyk, S. Zadrożny, Soft computing and web intelligence for supporting consensus reaching, Soft Computing 14 (2010) 833–846,.
[23]
C.W. Karvetski, K.C. Olson, D.R. Mandel, C.R. Twardy, Probabilistic coherence weighting for optimizing expert forecasts, Decision Analysis 10 (4) (2013) 305–326,.
[24]
R.L. Keeney, Foundations for group decision analysis, Decision Analysis 10 (2) (2013) 103–120,.
[25]
C.C. Li, Y. Gao, Y.C. Dong, Managing ignorance elements and personalized individual semantics under incomplete linguistic distribution context in group decision making, Group Decision and Negotiation 30 (1) (2021) 97–118,.
[26]
C.C. Li, Y.C. Dong, W. Pedrycz, F. Herrera, Integrating continual personalized individual semantics learning in consensus reaching in linguistic group decision making, IEEE Transactions on Systems, Man, and Cybernetics 52 (2022) (2022) 1525–1536,.
[27]
J.P. Liu, X.W. Liao, W.H. Zhao, N. Yang, A classification approach based on the outranking model for multiple criteria ABC analysis, Omega 61 (2016) 19–34,.
[28]
F. Liu, Y.H. Wu, W. Pedrycz, A modified consensus model in group decision making with an allocation of information granularity, IEEE Transactions on Fuzzy Systems 26 (5) (2018) 3182–3187,.
[29]
Y.T. Liu, Y.C. Dong, H.M. Liang, F. Chiclana, E. Herrera-Viedma, Multiple attribute strategic weight manipulation with minimum cost in a group decision making context with interval attribute weights information, IEEE Transactions on Systems, Man, and Cybernetics: Systems 49 (10) (2019) 1981–1992,.
[30]
Y.T. Liu, H.J. Zhang, Y.Z. Wu, Y.C. Dong, Ranking range based approach to MADM under incomplete context and its application in venture investment evaluation, Technological and Economic Development of Economy 25 (5) (2019) 877–899,.
[31]
Y.T. Liu, Y. Li, Z. Zhang, Y. Xu, Y.C. Dong, Classification-based strategic weight manipulation in multiple attribute decision making, Expert Systems with Applications 197 (2022).
[32]
F. Liu, L. Tong, Y.R. Chen, A consensus building model in group decision making with non-reciprocal fuzzy preference relations, Complex & Intelligent Systems, in press (2022),.
[33]
M. Mohammadi, J. Rezaei, Bayesian best-worst method: A probabilistic group decision making model, Omega-International Journal of Management Science 96 (2020),.
[34]
I. Palomares, L. Martínez, F. Herrera, A consensus model to detect and manage noncooperative behaviors in large-scale group decision making, IEEE Transactions on Fuzzy Systems 22 (3) (2014) 516–530,.
[35]
D.A. Pelta, R.R. Yager, Decision strategies in mediated multiagent negotiations: An optimization approach, IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans 40 (3) (2010) 635–640,.
[36]
I.J. Pérez, F.J. Cabrerizo, E. Herrera-Viedma, A mobile decision support system for dynamic group decision-making problems, IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans 40 (6) (2010) 1244–1256,.
[37]
W. Pedrycz, M.L. Song, Analytic hierarchy process (AHP) in group decision making and its optimization with an allocation of information granularity, IEEE Transactions on Fuzzy Systems 19 (3) (2011) 527–539,.
[38]
T.L. Saaty, A scaling method for priorities in hierarchical structures, Journal of Mathematical Psychology 15 (3) (1977) 234–281,.
[39]
T.L. Saaty, Decision making for leaders: The analytic hierarchy process for decisions in a complex world, RWS (1990) publications.
[40]
J. Wu, M.S. Cao, F. Chiclana, Y.C. Dong, E. Herrera-Viedma, An optimal feedback model to prevent manipulation behaviors in consensus under social network group decision making, IEEE Transactions on Fuzzy Systems 29 (7) (2020) 1750–1763,.
[41]
S.Q. Wu, M. Wu, Y.C. Dong, H.M. Liang, S.H. Zhao, The 2-rank additive model with axiomatic design in multiple attribute decision making, European Journal of Operational Research 287 (2) (2020) 536–545,.
[42]
J. Xiao, X.L. Wang, H.J. Zhang, Managing classification-based consensus in social network group decision making: An optimization-based approach with minimum information loss, Information Fusion 63 (2020) 74–87,.
[43]
X.H. Xu, Z.J. Du, X.H. Chen, Consensus model for multi-criteria large-group emergency decision making considering non-cooperative behaviors and minority opinions, Decision Support Systems 79 (2015) 150–160,.
[44]
W.J. Xu, X. Chen, Y.C. Dong, F. Chiclana, Impact of decision rules and non-cooperative behaviors on minimum consensus cost in group decision making, Group Decision and Negotiation 30 (6) (2021) 1239–1260,.
[45]
R.R. Yager, On ordered weighted averaging aggregation operators in multi-criteria decision making, IEEE Transactions on Systems, Man, and Cybernetics 18 (1) (1988) 183–190,.
[46]
R.R. Yager, Penalizing strategic preference manipulation in multi-agent decision making, IEEE Transactions on Fuzzy Systems 9 (3) (2001) 393–403,.
[47]
R.R. Yager, Defending against strategic manipulation in uninorm-based multi-agent decision making, European Journal of Operational Research 141 (1) (2002) 217–232,.
[48]
R.R. Yager, OWA aggregation with an uncertainty over the arguments, Information Fusion 52 (2019) 206–212,.
[49]
B.W. Zhang, H.M. Liang, G.Q. Zhang, Reaching a consensus with minimum adjustment in MAGDM with hesitant fuzzy linguistic term sets, Information Fusion 42 (2018) 12–23,.
[50]
H.J. Zhang, Y.C. Dong, X. Chen, The 2-rank consensus reaching model in the multi-granular linguistic multiple-attribute group decision making, IEEE Transactions on Systems, Man, and Cybernetics: Systems 48 (12) (2018) 2080–2094,.
[51]
B.W. Zhang, Y.C. Dong, E. Herrera-Viedma, Group decision making with heterogeneous preference structures: An automatic mechanism to support consensus reaching, Group Decision and Negotiation 28 (3) (2019) 585–617,.
[52]
B.W. Zhang, Y.C. Dong, H.J. Zhang, W. Pedrycz, Consensus mechanism with maximum-return modifications and minimum-cost feedback: A perspective of game theory, European Journal of Operational Research 287 (2) (2020) 546–559,.
[53]
Z. Zhang, J. Gao, Y. Gao, W. Yu, Two-sided matching decision making with multi-granular hesitant fuzzy linguistic term sets and incomplete criteria weight information, Expert Systems with Applications 168 (2021),.
[54]
Z. Zhang, Z. Li, Y. Gao, Consensus reaching for group decision making with multi-granular unbalanced linguistic information: A bounded confidence and minimum adjustment-based approach, Information Fusion 74 (2021) 96–110,.
[55]
Z. Zhang, Z. Li, Personalized individual semantics-based consistency control and consensus reaching in linguistic group decision making, IEEE Transactions on Systems, Man, and Cybernetics: Systems. (2022),.

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Published In

cover image Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal  Volume 216, Issue C
Apr 2023
1126 pages

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Pergamon Press, Inc.

United States

Publication History

Published: 15 April 2023

Author Tags

  1. Group decision making (GDM)
  2. 2-Rank
  3. Consensus level
  4. Strategic experts’ weight manipulation

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