Double hierarchy linguistic term set and its extensions: The state‐of‐the‐art survey

Gou, Xunjie; Zhang, Xu

doi:10.1002/int.22323

Cited by 25 publications

(11 citation statements)

References 83 publications

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“…29 HFLTSs have attracted much attention from scholars and researchers in the decisionmaking field. 30 Many variants of HFLTSs have been put forward, such as the double hierarchy linguistic term set (LTS), 31,32 unbalanced HFLTS, 33 hesitant probabilistic fuzzy linguistic set, 34 and hesitant multiplicative LTSs. 35 HFLTSs have various applications, such as the evaluation of landfill sites, 36 medicine selection, 37 recommender system, 38 and healthcare service.…”

Section: Studies On Handling Hfltssmentioning

confidence: 99%

Evaluation of startup companies using multicriteria decision making based on hesitant fuzzy linguistic information envelopment analysis models

Lin

Chen

et al. 2021

Int J Intell Syst

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Evaluating startup companies is an important management process for technology business incubators and it is also a typical multicriteria decision‐making (MCDM) problem. There exist various methods that have proposed to solve MCDM problems, but these methods heavily depend on the exact criteria weight values. The decision results of these methods are unstable. Moreover, they cannot provide the improvement suggestions for the nonoptimal startup companies. To overcome these two drawbacks, we propose a novel hesitant fuzzy linguistic decision‐making method to solve the problem of evaluating startup companies. To this end, a novel semantic comparison method based on the experts' psychology and the ratio of score value to deviation degree is proposed to compare the hesitant fuzzy linguistic term sets. Then, a novel definition of hesitant fuzzy linguistic information envelopment efficiency (HFLIEE) is proposed, based on which, a novel hesitant fuzzy linguistic information envelopment analysis (HFLIEA) model and a novel preference model are proposed. By solving these models, all the alternatives can be ranked and nonoptimal alternatives can be improved. Finally, the numerical analysis is given to illustrate the applicability of the proposed models and the robustness analyses of the proposed models are provided. At the same time, they are compared with the previous hesitant fuzzy linguistic decision‐making methods.

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Section: Studies On Handling Hfltssmentioning

confidence: 99%

Evaluation of startup companies using multicriteria decision making based on hesitant fuzzy linguistic information envelopment analysis models

Lin

Chen

et al. 2021

Int J Intell Syst

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“…Unlike the single linguistic term set, the qualitative information can be expressed more flexibly by DHLTS, through complex linguistic expressions [ 12 ]. More importantly, DHLTS has been applied in many research areas [ 13 ], such as preference relations and decision making in the past few years. In 2020, Gou et al [ 14 ] proposed the concept of double hierarchy linguistic preference relations (DHLPR), considering that the pairwise comparison methods are more accurate than nonpairwise methods because experts only need to focus exclusively on two alternatives at a time [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

“…Recently, with comprehensive analysis of damage assessment process of anti-missile against ships, a synthetic damage effectiveness assessment process is proposed based on DHLTS and the evidence theory by Yao et al [ 25 ]. With the in-depth study of DHLTS, some of its extensions in recent years have been continuously developed, including unbalanced DHLTS (UDHLTS) [ 26 ], DHLPR [ 13 ] and double hierarchy hesitant fuzzy linguistic term set (DHHFLTS) [ 27 ], etc. In conclusion, DHLTS is an important topic for linguistic model research and it also has some good advantages for processing the complex language information.…”

Section: Introductionmentioning

confidence: 99%

A three-way decisions approach based on double hierarchy linguistic aggregation operators of strict t-norms and t-conorms

Zhong

Chen

et al. 2023

Int. J. Mach. Learn. & Cyber.

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With the massive increase in uncertainty of linguistic information in realistic decision making, there is a great challenge for people to make decisions in the complex linguistic environment. To overcome this challenge, this paper proposes a three-way decisions method based on aggregation operators of strict t-norms and t-conorms under double hierarchy linguistic environment. By mining the double hierarchy linguistic information, strict t-norms and t-conorms are introduced to define the operation rules and their operation examples are also given. Then, the double hierarchy linguistic weighted average (DHLWA) operator and weighted geometric (DHLWG) operator are proposed based on strict t-norms and t-conorms. Besides, some of their important properties are also proved and derived, such as idempotency, boundedness and monotonicity. Next, DHLWA and DHLWG are integrated with three-way decisions to construct our three-way decisions model. Specifically, the double hierarchy linguistic decision theoretic rough set (DHLDTRS) model is constructed by incorporating the computational model of expected loss with DHLWA and DHLWG, which can consider the various decision attitudes from decision makers more adequately. Furthermore, we also propose a novel entropy weight calculation formula to improve the entropy weight method for obtaining the weights more objectively, and integrate grey relational analysis (GRA) method to calculate the conditional probability. Based on the Bayesian minimum-loss decision rules, the solving method of our model is also propounded and the corresponding algorithm is designed. Finally, an illustrative example and experimental analysis are presented, which can validate the rationality, robustness as well as superiority of our method.

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“…. Gou et al [11] give the idea of a double hierarchy linguist term set (DHLTS). Decision-making is an art, and many researchers have worked on this aspect, see [12][13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Identification of the Best Sector for Multinatinal Companies Investment Using the Q-rung Double Hierarchy Linguistic Term Set Todim Approach

Hong-bin

Gulistan

Mahmood

et al. 2023

Preprint

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The Multinational Companies started with the rise of colonialism in the world. As a major drive of colonialism, the early multinational corporations built "factories" in the port cities of colonized countries. Now, Multinational Companies (MNCs) are investing in different sectors of the economy. However, asset allocation decisions still require proper investigation of industries and countries where the MNCs must invest. Moreover, decision-making becomes more difficult due to incomplete data, uncertainty, psychological and cultural issues in different countries, and hesitancy of the decision-makers (DMs). To overcome these issues, sophisticated decision-making techniques must be employed, so we propose the TODIM approach under the environment of q-rung orthopair double hierarchy linguistic term set (q-RODHLTS), which is the hybrid of q-rung orthopair fuzzy set and double hierarchy linguistic term set. Further, we define basic operations like addition, multiplication, scalar multiplication, exponential, and the comparison functions and distance of q-RODHLT sets. Finally, some applications related to the different sectors for investment by a multinational company (MNC), such as Tourism, energy, and education, are presented using the proposed approaches with comparative analysis. We conclude that energy is the best sector for investment by the MNCs. 1991 Mathematics Subject Classification. 03E72, 03B52, 90C70, 47S40, 15B15.

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Double hierarchy linguistic term set and its extensions: The state‐of‐the‐art survey

Cited by 25 publications

References 83 publications

Evaluation of startup companies using multicriteria decision making based on hesitant fuzzy linguistic information envelopment analysis models

Evaluation of startup companies using multicriteria decision making based on hesitant fuzzy linguistic information envelopment analysis models

A three-way decisions approach based on double hierarchy linguistic aggregation operators of strict t-norms and t-conorms

Identification of the Best Sector for Multinatinal Companies Investment Using the Q-rung Double Hierarchy Linguistic Term Set Todim Approach

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