Some Maclaurin Symmetric Mean Aggregation Operators Based on Cloud Model and Their Application to Decision-Making

Peide Liu, Hongyu Yang, Haiquan Wu (), Meilong Ju and Fawaz E. Alsaadi
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Peide Liu: School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan Shandong 250014, P. R. China
Hongyu Yang: School of Management Science and Engineering, Shandong University of Finance and Economics, Jinan Shandong 250014, P. R. China
Haiquan Wu: #x2020;Business School, Central South University, Hunan, Changsha 410083, P. R. China
Meilong Ju: #x2021;Information Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan Shandong 250353, P. R. China
Fawaz E. Alsaadi: #xA7;Department of Information Technology, Faculty of Computing and IT, King Abdulaziz University, Jeddah, Saudi Arabia

International Journal of Information Technology & Decision Making (IJITDM), 2019, vol. 18, issue 03, 981-1007

Abstract: The cloud model (CM) is an important tool to describe qualitative concept by the quantitative method, and the Maclaurin symmetric mean (MSM) can capture the interrelationship among the multi-inputs and it can generalize most of existing operators. In this paper, we firstly convert the uncertain linguistic variables (ULVs), which are easily used to express the qualitative information, to CM. Then, we combine the MSM with the CM, and propose the cloud MSM (CMSM) operator and cloud weighted MSM (CWMSM) operator. In addition, we explore some of their desirable features and develop a new approach to deal with some multi-attribute group decision-making (MAGDM) problems under the uncertain environment based on the proposed operators. Finally, by comparing with other approaches, an illustrative example is arranged to demonstrate the usability of the proposed method.

Keywords: Uncertain linguistic variables; cloud model; Maclaurin symmetric mean; MAGDM (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1142/S0219622019500135

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