A Personalized Comprehensive Cloud-Based Method for Heterogeneous MAGDM and Application in COVID-19

IF 2.2 4区工程技术 Q2 ENGINEERING, MULTIDISCIPLINARY

Cmes-computer Modeling in Engineering & Sciences Pub Date : 2022-01-01 DOI:10.32604/cmes.2022.019501

Xiao-Bing Mao, Hao Wu, S. Wan

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引用次数: 6

Abstract

This paper proposes a personalized comprehensive cloud-based method for heterogeneous multi-attribute group decision-making (MAGDM), in which the evaluations of alternatives on attributes are represented by LTs (linguistic terms), PLTSs (probabilistic linguistic term sets) and LHFSs (linguistic hesitant fuzzy sets). As an effective tool to describe LTs, cloud model is used to quantify the qualitative evaluations. Firstly, the regulation parameters of entropy and hyper entropy are defined, and they are further incorporated into the transformation process from LTs to clouds for reflecting the different personalities of decision-makers (DMs). To tackle the evaluation information in the form of PLTSs and LHFSs, PLTS and LHFS are transformed into comprehensive cloud of PLTS (C-PLTS) and comprehensive cloud of LHFS (C-LHFS), respectively. Moreover, DMs' weights are calculated based on the regulation parameters of entropy and hyper entropy. Next, we put forward cloud almost stochastic dominance (CASD) relationship and CASD degree to compare clouds. In addition, by considering three perspectives, a comprehensive tri-objective programing model is constructed to determine the attribute weights. Thereby, a personalized comprehensive cloud-based method is put forward for heterogeneous MAGDM. The validity of the proposed method is demonstrated with a site selection example of emergency medical waste disposal in COVID-19. Finally, sensitivity and comparison analyses are provided to show the effectiveness, stability, flexibility and superiorities of the proposed method.

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基于云的异构MAGDM个性化综合方法及在COVID-19中的应用

本文提出了一种基于个性化综合云的异构多属性群体决策(MAGDM)方法，该方法采用语言项(LTs)、概率语言项集(plts)和语言犹豫模糊集(lhfs)来表示属性选项的评价。云模型作为一种有效的描述LTs的工具，用于量化定性评价。首先，定义了熵和超熵的调节参数，并将其进一步纳入到从lt到云的转变过程中，以反映决策者的不同性格。为了处理PLTS和LHFS形式的评价信息，将PLTS和LHFS分别转化为PLTS综合云(C-PLTS)和LHFS综合云(C-LHFS)。此外，根据熵和超熵的调节参数计算dm的权值。其次，我们提出了云的几乎随机优势关系(CASD)和CASD度来比较云。此外，从三个角度考虑，构建了一个综合的三目标规划模型来确定属性权重。从而提出了一种基于云的异构MAGDM的个性化综合方法。以2019冠状病毒病应急医疗废物处置选址为例，验证了该方法的有效性。最后，通过灵敏度分析和对比分析，验证了该方法的有效性、稳定性、灵活性和优越性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cmes-computer Modeling in Engineering & Sciences ENGINEERING, MULTIDISCIPLINARY-MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

CiteScore

3.80

自引率

16.70%

发文量

298

审稿时长

7.8 months

期刊介绍： This journal publishes original research papers of reasonable permanent value, in the areas of computational mechanics, computational physics, computational chemistry, and computational biology, pertinent to solids, fluids, gases, biomaterials, and other continua. Various length scales (quantum, nano, micro, meso, and macro), and various time scales ( picoseconds to hours) are of interest. Papers which deal with multi-physics problems, as well as those which deal with the interfaces of mechanics, chemistry, and biology, are particularly encouraged. New computational approaches, and more efficient algorithms, which eventually make near-real-time computations possible, are welcome. Original papers dealing with new methods such as meshless methods, and mesh-reduction methods are sought.

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