Multi-stage consistency optimization algorithm for decision making with incomplete probabilistic linguistic preference relation

Wang, Peng; Лю, Пэйдэ; Chiclana, Francisco

doi:10.1016/j.ins.2020.10.004

Cited by 78 publications

(34 citation statements)

References 52 publications

(200 reference statements)

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“…Because the amount of complete and used blockchain is too large, in this paper, we build a blockchain that takes Taifang's private chain as a prototype system to store tracking information. is paper will implement and verify the license chain P2P network [19] and consistency algorithm designed [20]. e license chain of the prototype system is shown in Figure 3.…”

Section: Implementation Of License Chainmentioning

confidence: 99%

Design and Implementation of Data Sharing Traceability System Based on Blockchain Smart Contract

Kang

2021

Scientific Programming

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“Traceability” is an important method often used in modern supply management. The traceability system is a system based on the Internet of Things technology. In this process, users will share resources through cloud service providers, so how to ensure data security is also one of the issues we consider. Blockchain technology is an emerging technology in the field of information technology. Its decentralized nature, distributed storage, and difficult data modification provide us with fair exchange and sharing of data. Feasible solutions: in this article, we have studied the key issues of fair exchange and safe sharing of data based on blockchain and designed a multigroup data sharing scheme based on alliance chain. To solve the various existing traceability systems problem, this paper designs a new traceability system based on blockchain technology and implements a system prototype to verify the feasibility of the system.

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Section: Implementation Of License Chainmentioning

confidence: 99%

Design and Implementation of Data Sharing Traceability System Based on Blockchain Smart Contract

Kang

2021

Scientific Programming

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“…In practice, the performance of alternatives under some criteria is too complex for experts to give a clear evaluation [14,15]. At this time, pairwise comparison between alternatives is a good choice for decision makers to express preference.…”

Section: Introductionmentioning

confidence: 99%

“…At this time, pairwise comparison between alternatives is a good choice for decision makers to express preference. Probabilistic linguistic preference relation (PLPR) [14] is the most prominent one among all linguistic preference relations [15], which expresses experts' preference for one alternative over another through PLTSs. PLTSs can fully represent the information of decision makers, which allows decision makers to select multiple linguistic terms and give corresponding probabilities to express importance [2].…”

Section: Introductionmentioning

confidence: 99%

“…However, Liao et al [20] did not consider the specific situation of missing value, and simply expressed PLTS with missing information as unknown quantity. Wang et al [15] thought InPLTS should be divided into missing linguistic term-InPLTS (MLT-InPLTS) and the missing probability-InPLTS (MP-InPLTS), and designed two-stage optimization process based on expected multiplicative consistency and information entropy to estimate missing linguistic terms and missing probabilities at the same time. However, Wang et al [15] only considered missing single linguistic term in InPLTSs, and did not realize that experts might be hesitant and uncertain about multiple linguistic terms.…”

Section: Introductionmentioning

confidence: 99%

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Additive Consistency-Based Decision-Making with Incomplete Probabilistic Linguistic Preference Relations

Chen

Xiao

Deng

et al. 2021

Int. J. Fuzzy Syst.

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Probabilistic linguistic term set (PLTS), an efficient tool to describe decision information, can sufficiently express decision makers' hesitation and preference. Probabilistic linguistic preference relation (PLPR) is based on PLTSs to describe the preference information of experts for paired alternatives. However, in practice, due to the complexity of the problem, the incompleteness of information and the lack of professional knowledge, the incomplete PLPR (InPLPR) with missing information often appears. Therefore, this paper proposes a decision-making method under InPLPR. Firstly, in order to fully consider the specific situation of missing values, missing linguistic term-InPLTS (MLT-InPLTS) is subdivided into missing single linguistic term-InPLTS (MSLT-InPLTS) and missing multiple linguistic terms-InPLTS (MMLT-InPLTS). Then, a two-stage mathematical optimization model of missing information estimation based on additive consistency, fuzzy entropy and hesitation entropy is established. Subsequently, aiming at the unacceptable consistency of complete PLPR (CPLPR) after filling in the missing values, a consistency improvement method based on the idea of gradient descent is proposed. Afterward, probabilistic linguistic weighted averaging (PLWA) operator is used to rank alternatives. Finally, medical supplier selection is taken as an example to verify the effectiveness of the proposed decision-making method, and the robustness and advantages of this method are illustrated by sensitivity analysis and comparison with other methods.

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“…In addition, in terms of qualitative evaluation, the linguistic variables (LVs) introduced by Zadeh [9] promote the convenient expression of qualitative information, which is more in line with human evaluation habits. Then, some scholars point out that a single linguistic term (LT) is not enough to accurately model the qualitative evaluation information, so some extended linguistic information forms begin to emerge, such as two-dimensional linguistic variables (2DLVs) [10], hesitant fuzzy linguistic term sets [11], probabilistic linguistic term sets [12,13], and so on. However, it is worth noting that in the real complex decision-making environment, if people want to describe some uncertain information more accurately and completely, it is necessary to consider both qualitative and quantitative expressions.…”

Section: Introductionmentioning

confidence: 99%

Extended VIKOR-QUALIFLEX Method Based on Trapezoidal Fuzzy Two-Dimensional Linguistic Information for Multiple Attribute Decision-Making with Unknown Attribute Weight

Liu

2020

Mathematics

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Considering the advantages of trapezoid fuzzy two-dimensional linguistic variables (TrF2DLVs), which can not only accurately describe the qualitative evaluation but also use qualitative linguistic variables (LVs) to describe the confidence level of this evaluation in the second dimension, this paper proposes a novel method based on trapezoidal fuzzy two-dimensional linguistic information to solve multiple attribute decision-making (MADM) problems with unknown attribute weight. First, a combination weight model is constructed, which covers a subjective weight determination model based on the proposed trapezoidal fuzzy two-dimensional linguistic best-worst method (TrF2DL-BWM) and an objective weight determination model based on the proposed CRITIC method. Then, in order to accurately rank the alternatives, an extended VIKOR-QUALIFLEX method is proposed, which can measure the concordance index of each ranking combination by means of group utility and individual maximum regret value of each evaluation alternative. Finally, a practical problem of lean management assessment for industrial residential projects is solved by the proposed method, and the effectiveness and advantages of the method are demonstrated by comparative analysis and discussion.

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Multi-stage consistency optimization algorithm for decision making with incomplete probabilistic linguistic preference relation

Cited by 78 publications

References 52 publications

Design and Implementation of Data Sharing Traceability System Based on Blockchain Smart Contract

Design and Implementation of Data Sharing Traceability System Based on Blockchain Smart Contract

Additive Consistency-Based Decision-Making with Incomplete Probabilistic Linguistic Preference Relations

Extended VIKOR-QUALIFLEX Method Based on Trapezoidal Fuzzy Two-Dimensional Linguistic Information for Multiple Attribute Decision-Making with Unknown Attribute Weight

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