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Linguistic multi-criteria decision-making with representing semantics by programming

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  • Wu-E Yang
  • Chao-Qun Ma
  • Zhi-Qiu Han

Abstract

A linguistic multi-criteria decision-making method is introduced. In this method, a maximising discrimination programming assigns the semanteme values to linguistic variables to represent their semantics. Incomplete preferences from using linguistic information are expressed by the constraints of the model. Such assignment can amplify the difference between alternatives. Thus, the discrimination of the decision model is increased, which facilitates the decision-maker to rank or order the alternatives for making a decision. We also discuss the parameter setting and its influence, and use an application example to illustrate the proposed method. Further, the results with three types of semantic structure highlight the ability of the method in handling different semantic structures.

Suggested Citation

  • Wu-E Yang & Chao-Qun Ma & Zhi-Qiu Han, 2017. "Linguistic multi-criteria decision-making with representing semantics by programming," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(2), pages 225-235, January.
    • Handle: RePEc:taf:tsysxx:v:48:y:2017:i:2:p:225-235
    DOI: 10.1080/00207721.2016.1177129
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    References listed on IDEAS

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    Cited by:

    1. Wenyu Yu & Zhen Zhang & Qiuyan Zhong, 2021. "Consensus reaching for MAGDM with multi-granular hesitant fuzzy linguistic term sets: a minimum adjustment-based approach," Annals of Operations Research, Springer, vol. 300(2), pages 443-466, May.

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