A Method for Multi-Criteria Group Decision Making with 2-Tuple Linguistic Information Based on Cloud Model

Abstract

This paper presents a new approach to solve the multi-criteria group decision making (MCGDM) problem where criteria values take the form of 2-tuple linguistic information. Firstly, a 2-tuple hybrid ordered weighted geometric (THOWG) operator is proposed, which synthetically considers the importance of both individual and the ordered position so as to overcome the defects of existing operators. Secondly, combining the advantages of the cloud model and 2-tuple linguistic variable, a new generating cloud method is proposed to transform 2-tuple linguistic variables into clouds. Thirdly, we further define some new cloud algorithms, such as cloud possibility degree and cloud support degree which can be respectively used to compare clouds and determine the criteria weights. Furthermore, a new approach for 2-tuple linguistic group decision making is presented on the basis of the THOWG operator, the improved generating cloud method as well as the new cloud algorithms. Finally, an example of assessing the social effects of biomass power plants (BPPS) is illustrated to verify the application and feasible of the developed approach, and a comparative analysis is also conducted to validate the effectiveness of the proposed method.

Risk-Based Multi-Attribute Decision-Making for Normal Cloud Model Considering Pre-Evaluation Information

“…Where in (9) Hei = 0. Furthermore, the same as the idea illustrated in (8), (9) is also the relative distance which has three properties.…”

“…Three numerical characteristics are utilized to describe one cloud model [6], [8]: expectation, entropy, and hyper entropy, which can explicitly disclose the randomness and the fuzziness of qualitative concepts. Up to now, cloud model is considered one of the most effective tools for handling linguistic expressions, and normal cloud model is mainly utilized for handling various linguistic expressions [9]- [12]. Moreover, normal cloud model can be also used to depict quantitative things with fuzziness and randomness being included, such as interval numbers [13].…”