Two-level consensus modeling with utility and cost constraints

doi:10.23919/JSEE.2022.000066

Journal of Systems Engineering and Electronics ›› 2022, Vol. 33 ›› Issue (3): 716-726.doi: 10.23919/JSEE.2022.000066

收稿日期:2020-12-21 出版日期:2022-06-18 发布日期:2022-06-24

Two-level consensus modeling with utility and cost constraints

Weixue DIAO(), Yong LIU*()

¹ School of Business, Jiangnan University, Wuxi 214122, China

Received:2020-12-21 Online:2022-06-18 Published:2022-06-24
Contact: Yong LIU E-mail:6190903002@stu.jiangnan.edu.cn;clly1985528@163.com
About author:|DIAO Weixue was born in 1996. She is studying for her M.S. degree at Jiangnan University. Her research interests are group decision making and conflict analysis.E-mail: 6190903002@stu.jiangnan.edu.cn||LIU Yong was born in 1985. He received his B.S., M.S., and Ph.D degrees in mechanical engineering, system engineering, and management science and engineering from Nanjing University of Aeronautics and Astronautics. Currently, he is an associate professor at the Business School, Jiangnan University . His research interests are conflict analysis, soft computing, and grey system. E-mail: clly1985528@163.com
Supported by:
This work was supported by the National Natural Science Foundation of China (71503103), the Outstanding Youth in Social Sciences of Jiangsu Province, and the Jiangsu Qinglan Project and the Tender Project from Wuxi Federation of Philosophy and Social Sciences (WXCK22-A-03)

摘要/Abstract

Abstract:

There exist many two-level group consensus problems with different psychological behaviors of decision makers. To deal with these group consensus problems and reach a stable consensus, based on the principles and methods of grey system, utility theory and group consensus, we use grey utility function to describe and reflect decision makers’ opinion preferences in different subgroups and different levels, and then we construct a two-level group consensus method with a moderator, and exploit it to solve the negotiation problems of the natural gas subsidy.

Key words: two-level group consensus, group negotiation, utility function, natural gas subsidy

. [J]. Journal of Systems Engineering and Electronics, 2022, 33(3): 716-726.

Weixue DIAO, Yong LIU. Two-level consensus modeling with utility and cost constraints[J]. Journal of Systems Engineering and Electronics, 2022, 33(3): 716-726.

图/表 8

参考文献 35

1	GONG Z W, XU X X, LI L S, et al. Consensus modeling with nonlinear utility and cost constraints. Knowledge-Based Systems, 2015, 88, 210- 222.
2	CHOI J H, AHN H, HAN I Utility-based double auction mechanism using genetic algorithms. Expert Systems with Applications, 2008, 34 (1): 150- 158.
3	GONG Z W, XU C, CHICLANA F, et al Consensus measure with multi-stage fluctuation utility based on China’s urban demolition negotiation. Group Decision and Negotiation, 2017, 26 (2): 379- 407.
4	HOCHBAUM D S, LEVIN A Methodologies and algorithms for group-levelings decision. Management Science, 2006, 52 (9): 1394- 1408.
5	DONG Q X, COOPER O A peer-to-peer dynamic adaptive consensus reaching model for the group AHP decision making. European Journal of Operational Research, 2016, 250 (2): 521- 530.
6	HINSZ V B Cognitive and consensus processes in group recognition memory performance. Journal of Personality and Social Psychology, 1990, 59 (4): 705- 718.
7	LI Y, ZHANG H J, DONG Y C The interactive consensus reaching process with the minimum and uncertain cost in group decision making. Applied Soft Computing, 2017, 60, 202- 212.
8	MENG F Y, AN Q X, CHEN X H A consistency and consensus-based method to group decision making with interval linguistic preference relations. Journal of the Operational Research Society, 2016, 67 (11): 1419- 1437.
9	PARREIRAS R, EKEL P Y, MORAIS D C, et al Fuzzy set based consensus schemes for multicriteria group decision making applied to strategic planning. Group Decision and Negotiation, 2012, 21 (2): 153- 183.
10	ZHANG F, IGNATIUS J, LIM C P, et al A two-stage dynamic group decision making method for processing ordinal information. Knowledge-Based Systems, 2014, 70, 189- 202.
11	DONG Y C, CHEN X, HERRERA F Minimizing adjusted simple terms in the consensus reaching process with hesitant linguistic assessments in group decision making. Information Science, 2015, 297, 95- 117.
12	DONG Y C, XU J P. Consensus building in group decision making. Singapore: Springer, 2015.
13	ZHANG H J, DONG Y C, CHICLANA F, et al Consensus efficiency in group decision making: a comprehensive comparative study and its optimal design. European Journal of Operational Research, 2019, 275 (2): 580- 598.
14	HERRERAVIEDMA E, HERRERA F, CHICLANA F A consensus model for multi-person decision making with different preference structures. IEEE Trans. on Systems, Man and Cybernetics, 2002, 32 (3): 394- 402.
15	DONG Y C, ZHANG H J Multi-person decision making with different preference representation structures: a direct consensus framework and its properties. Knowledge-Based Systems, 2014, 58, 45- 57.
16	ZHANG N, GONG Z W, CHICLANA F Minimum cost consensus models based on random opinions. Expert Systems with Applications, 2017, 89, 149- 159.
17	LIU J, CHAN F T, LI Y, et al Short communication: a new optimal consensus method with minimum cost in fuzzy group decision. Knowledge-Based Systems, 2012, 35, 357- 360.
18	TANINO T. Multi-person decision making models using fuzzy sets and possibility theory on group decision making under fuzzy preferences. Dordrecht: Springer, 1990.
19	KACPRZYK J, FEDRIZZI M, NURMI H Group decision making and consensus under fuzzy preferences and fuzzy majority. Fuzzy Sets and Systems, 1992, 49 (1): 21- 31.
20	CELOTTO A, LOIA V, SENATORE S Fuzzy linguistic approach to quality assessment model for electricity network infrastructure. Information Sciences, 2015, 304, 1- 15.
21	ORLOVSKY S A Decision-making with a fuzzy preference relation. Fuzzy Sets and Systems, 1978, 1 (3): 155- 167.
22	CAO M, WU J, CHICLANA F, et al A personalized consensus feedback mechanism based on maximum harmony degree. IEEE Trans. on Systems, 2021, 51 (10): 6134- 6146.
23	XIAO T, GONG Z W, FRANCISCO C, et al Consensus modeling with cost chance constraint under uncertainty opinions. Applied Soft Computing, 2018, 67, 721- 727.
24	ZHANG B W, DONG Y C, ZHANG H J, et al Consensus mechanism with maximum-return modifications and minimum-cost feedback: a perspective of game theory. European Journal of Operational Research, 2020, 287 (2): 546- 559.
25	XU W J, CHEN X, DONG Y C, et al Impact of decision rules and non-cooperative behaviors on minimum consensus cost in group decision making. Group Decision and Negotiation, 2021, 30 (6): 1239- 1260.
26	GONG Z W, XU X X, LU F L. et al On consensus models with utility preferences and limited budget. Applied Soft Computing, 2015, 35, 840- 849.
27	TAN X, GONG Z W, CHICLANA F, et al Consensus modeling with cost chance constraint under uncertainty opinions. Applied Soft Computing. Applied Soft Computing, 2015, 67, 721- 727.
28	KACPRZYK J, ZADROZNY S. On a fairness type approach to consensus reaching support under fuzziness via linguistic summaries. Proc. of the IEEE International Conference on Fuzzy Systems, 2016. DOI: 10.1109/FUZZ-IEEE.2016.7737937.
29	SWIECHOWSKI M, KACPRZYK J, ZADROZNY S. A novel game playing based approach to the modeling and support of consensus reaching in a group of agents. Proc. of the IEEE Symposium Series on Computational Intelligence, 2016:1–8. DOI: 10.1109/SSCI.2016.7850032.
30	CASTAGNOLI E, CALZI M L Expected utility without utility. Theory and Decision, 1996, 41 (3): 281- 301.
31	BECCACECE F, BORGONOVO E Functional ANOVA, ultramodularity and monotonicity: Applications in multi-attribute utility theory. European Journal of Operational Research, 2011, 210 (2): 326- 335.
32	LIU S F. Grey system theory and its application (the eighth edition). Beijing: Science Press, 2016.
33	FENG B, LAI F J Multi-attribute group decision making with aspirations: a case study. Omega-international Journal of Management Science, 2014, 44, 136- 147.
34	BEN-ARIEH D, EASTON T Multi-criteria group consensus under linear cost opinion elasticity. Decision Support Systems, 2007, 43 (3): 713- 721.
35	BEN-ARIEH D, EASTON T，EVANS B Minimum cost consensus with quadratic cost functions. IEEE Trans. on Systems, Man, and Cybernetics - Part A: Systems and Humans, 2009, 39 (1): 210- 217.

o_ij	$ {c_1}^j $	$ {a_l} $	$ {a_1} $	$o_{ij} $	$ {c_2}^j $	$ {a_l} $	$ {a_1} $
$ {o_{11}} $	1 11	6	23	$ {o_{11}} $	1	5	25
$ {o_{12}} $	2	3	16	$ {o_{12}} $	2	3	22
$ {o_{13}} $	3	5	18	$ {o_{13}} $	1	7	24
$ {o_{14}} $	1	4	19	$ {o_{14}} $	3	2	25

Two-level consensus modeling with utility and cost constraints

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 8

参考文献 35

相关文章 0

编辑推荐

Metrics

本文评价