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Probabilistic linguistic decision-making based on the hybrid entropy and cross-entropy measures

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  • Bing Fang

    (Army Command College of PLA)

Abstract

In fuzzy decision-making, the probabilistic linguistic term sets (PLTSs) are flexible in depicting people’s linguistic evaluations. As the uncertainty measures of PLTSs, entropy and cross-entropy are the important decision-making tools. Generally speaking, the uncertainty of PLTSs can be studied from two facets, which are known as hesitancy and fuzziness. To better reflect these uncertainties, some hybrid entropy and cross-entropy measures of PLTSs are developed in this work. It is shown that the hybrid entropy measures are simple in structure, clear in physical meaning and strong in discriminating ability, while the hybrid cross-entropy measures can avoid the design flaws of existing measures and possess natural symmetry. It is also shown that the hybrid entropy and cross-entropy measures can be designed in pairs, mutually supportive and inherently unified as the uncertainty measures. In the ends, a multi-attribute decision-making (MADM) model, based on these uncertainty measures of PLTSs, is developed within the famous TOPSIS framework to select the best cloud computing platform.

Suggested Citation

  • Bing Fang, 2023. "Probabilistic linguistic decision-making based on the hybrid entropy and cross-entropy measures," Fuzzy Optimization and Decision Making, Springer, vol. 22(3), pages 415-445, September.
    • Handle: RePEc:spr:fuzodm:v:22:y:2023:i:3:d:10.1007_s10700-022-09398-9
    DOI: 10.1007/s10700-022-09398-9
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    References listed on IDEAS

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    1. Huchang Liao & Xiaomei Mi & Zeshui Xu, 2020. "A survey of decision-making methods with probabilistic linguistic information: bibliometrics, preliminaries, methodologies, applications and future directions," Fuzzy Optimization and Decision Making, Springer, vol. 19(1), pages 81-134, March.
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