2018
DOI: 10.1007/978-3-319-99695-0_40
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Multiple Criteria Group Decision-Making Based on Hesitant Fuzzy Linguistic Consensus Model for Fashion Sales Forecasting

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Cited by 5 publications
(2 citation statements)
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“…By mapping a 2-tuple linguistic (2TL) into an equivalent form, Wu and Xu (2016) presented an additive consistency index for HFLPR based on the distance between 2TL and the equivalent form, and then constructed a feedback mechanism with consensus to address the GDM. With the consistency measurement of HFLPR and ordinal numbers, the ordinal consensus was applied to build a consensus procedure (Tang & Liao, 2018). Furthermore, on the basis of discussing the worst consistency, additive consistency, multiplicative consistency of an HFLPR, various consensus models aiming to minimize the divergence between individuals and the group were proposed (Chen et al, 2020;Wu et al, 2019b;Zhang & Chen, 2019 The research on GDM with HFLPRs has great potential in theory and practice due to the superiority of HFLPRs in portraying fuzziness under uncertainty.…”
Section: Introductionmentioning
confidence: 99%
“…By mapping a 2-tuple linguistic (2TL) into an equivalent form, Wu and Xu (2016) presented an additive consistency index for HFLPR based on the distance between 2TL and the equivalent form, and then constructed a feedback mechanism with consensus to address the GDM. With the consistency measurement of HFLPR and ordinal numbers, the ordinal consensus was applied to build a consensus procedure (Tang & Liao, 2018). Furthermore, on the basis of discussing the worst consistency, additive consistency, multiplicative consistency of an HFLPR, various consensus models aiming to minimize the divergence between individuals and the group were proposed (Chen et al, 2020;Wu et al, 2019b;Zhang & Chen, 2019 The research on GDM with HFLPRs has great potential in theory and practice due to the superiority of HFLPRs in portraying fuzziness under uncertainty.…”
Section: Introductionmentioning
confidence: 99%
“…Quadro 5 -Classificação das aplicações dos estudos com DHFS.Yu, Zhang e Huang 2016;Qu et al, 2016;Wei, 2017;Ren, Xu and Wang, 2017;Yu, Li and Merigo, 2016;Zhao, Xu and Liu, 2016;Zhang, Li and Liao, 2018;Wei, 2017;Wang, Ding and Ding, 2016. Ju, Liu andSingh, 2017;Tang et al, 2017;Yang and Ju, 2014;Yang and Ju, 2015; Ye, 2014;Zang, Zhao and Li, 2018;Zang, Zhao and Li, 2018;Tang, Yang and Pedrycz, 2018;Chen, Xu and Yang, 2019;Gong and Chen, 2019;Jamil and Rashid, 2018;Ju, Zhang and Yang, 2014;Liang et al, 2020;Xu, Rui and Wang, 2015;Liang et al, 2019; Peng, Daí and Liu, 2018;Xue, Tang and Feng, 2016;Li, Zhuang and Ren, 2019. Fonte: Adaptado deCalache et al (2021a).Destaca-se que até o momento poucas técnicas multicritério foram combinadas com a abordagem DHF e poucos modelos de tomada de decisão foram propostos (LU;WANG;DING;DING, 2016;XU, 2016;ZHANG, 2016). As abordagens de consenso propostas até o momento estão relacionadas à diminuição entre as distâncias das avaliações entre os tomadores de decisão, e para isso, modelos de otimização vem sendo propostosMAITY et al, 2019).…”
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