A dynamically weight adjustment in the consensus reaching process for group decision-making with hesitant fuzzy preference relations

ABSTRACT

The consensus reaching process is a dynamic and iterative process for improving group's consensus level before making a final decision in group decision-making (GDM). As the experts will express their opinions under their own intellectual level from different aspects, it is natural that the experts’ weights should reflect their judgment information. This paper proposes a dynamic way to adjust weights of decision-makers (DMs) automatically when they are asked to give original judgment information for GDM problems, in which the DMs express their judgment information by hesitant fuzzy preference relations (HFPRs). Two indices, an individual consensus index of hesitant fuzzy preference relation (ICIHFPR) and a group consensus index of hesitant fuzzy preference relation (GCIHFPR), are introduced. Normalisation of HFPRs with different numbers of possible values is taken into consideration for better computation and comparison. An iterative consensus reaching algorithm is presented with DMs’ weighting vector changing in each consensus reaching process and the process terminates until both the ICIHFPR and GCIHFPR are controlled within predefined thresholds. Finally, an example is illustrated and comparative analyses demonstrate the effectiveness of the proposed methods.

KEYWORDS:

• Group decision-making
• consensus reaching process
• hesitant fuzzy preference relations
• dynamically weight adjustment

Acknowledgments

The authors are very grateful to Editor-in-Chief, Associate Editor and the anonymous reviewers for their constructive comments and suggestions that have further helped to improve the quality of this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was partly supported by the National Natural Science Foundation of China (NSFC) [grant number 71471056]; Key Project of National Natural Science Foundation of China [grant number 71433003]; Fundamental Research Funds for the Central Universities [grant number 2015B23014]; Excellent Innovative Talent Program of Hohai University, Qing Lan Project of Jiangsu Province.

Notes on contributors

Yejun Xu

Yejun Xu was born in 1979. He received the M.S. degree in 2005 and the Ph.D. degree in 2009, both in management science and engineering, both from Southeast University, China. Currently he is an associate professor with Business School, Hohai University. He has contributed more than 80 articles to professional journals, such as Fuzzy Sets and Systems, Information Sciences, International Journal of Approximate Reasoning, Knowledge-Based Systems, etc. His current research interests include information fusion, group decision-making under uncertainty.

Dou Rui

Dou Rui is a master student. His research interest is group decision-making.

Huimin Wang

Huimin Wang was born in 1963. She is now a professor with State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, and also a professor with Business School, Hohai University. She has contributed over 150 articles to professional journals. Her research interests include water resource management, management science and system engineering.