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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Peide Liu & Hongyu Yang & Haiquan Wu & Meilong Ju & Fawaz E. Alsaadi, 2019. "Some Maclaurin Symmetric Mean Aggregation Operators Based on Cloud Model and Their Application to Decision-Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(03), pages 981-1007, May.
    • Handle: RePEc:wsi:ijitdm:v:18:y:2019:i:03:n:s0219622019500135
    DOI: 10.1142/S0219622019500135
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    References listed on IDEAS

    as
    1. Peide Liu & Peng Wang, 2017. "Some Improved Linguistic Intuitionistic Fuzzy Aggregation Operators and Their Applications to Multiple-Attribute Decision Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 817-850, May.
    2. Peide Liu & Junlin Liu & Shyi-Ming Chen, 2018. "Some intuitionistic fuzzy Dombi Bonferroni mean operators and their application to multi-attribute group decision making," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(1), pages 1-24, January.
    3. Zeshui Xu, 2005. "An Approach To Pure Linguistic Multiple Attribute Decision Making Under Uncertainty," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 4(02), pages 197-206.
    4. Jian-qiang Wang & Juan-juan Peng & Hong-yu Zhang & Tao Liu & Xiao-hong Chen, 2015. "An Uncertain Linguistic Multi-criteria Group Decision-Making Method Based on a Cloud Model," Group Decision and Negotiation, Springer, vol. 24(1), pages 171-192, January.
    5. Yan, Hong-Bin & Ma, Tieju & Huynh, Van-Nam, 2017. "On qualitative multi-attribute group decision making and its consensus measure: A probability based perspective," Omega, Elsevier, vol. 70(C), pages 94-117.
    6. Merigó, José M. & Palacios-Marqués, Daniel & Zeng, Shouzhen, 2016. "Subjective and objective information in linguistic multi-criteria group decision making," European Journal of Operational Research, Elsevier, vol. 248(2), pages 522-531.
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