Large group decision-making based on interval rough integrated cloud model |
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| Affiliation: | 1. School of Microelectronics & Data Science, Anhui University of Technology, Ma’anshan, Anhui 243002, China;2. School of Mathematics, Thapar Institute of Engineering & Technology (Deemed University), Patiala 147004, Punjab, India;3. Department of Mathematics, Graphic Era Deemed to be University, Dehradun 248002, Uttarakhand, India;4. Applied Science Research Center, Applied Science Private University, Amman 11931, Jordan;5. College of Technical Engineering, The Islamic University, Najaf, Iraq;1. College of Mechanical Engineering, Tongji University, Shanghai 201804, China;2. Shanghai Metro Shield Machine Equipment & Engineering Co., Ltd, Shanghai 201804, China;1. 5-080 NREF, University of Alberta, 9105 116 St., Edmonton, Alberta T6G 2W2, Canada;2. Department of Engineering, Durham University, South Road, Durham DH1 3LE, UK;1. School of Mechanical Engineering, Hebei University of Technology, Tianjin 300130, China;2. National Technological innovation Method and Tool Engineering Research Center, Tianjin 300130, China;3. Yueqing Institute of Technological Innovation, Yueqing 325600, China |
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| Abstract: | Since different uncertainties exist in the large group decision-making (LGDM) process, such as randomness, diversity and fuzziness, a single method may be insufficient to address LGDM. Hence, this paper proposes a hybrid model that a new similarity calculation method for cloud model, the netting clustering and interval rough integrated cloud (IRIC) are combined to solve LGDM in uncertain linguistic environment. First, a new similarity method for cloud model is presented, based on which a netting clustering method is provided. The similarity calculation method has higher differentiation degree and has overcome some shortcomings of previous ones. Second, two hybrid-weighting methods are utilized respectively to calculate expert weights and attribute weights for making the decision-making process more credible and scientific. Finally, the IRIC method is applied to LGDM for dealing with the randomness and uncertainty. In addition, an example is offered to demonstrate the application of the proposed approach. According to a time-consuming test, the proposed method is more suitable to address LGDM in the big data environment. |
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| Keywords: | Large group decision-making Interval rough integrated cloud Similarity Cluster analysis Hybrid weights |
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