D-CFPR: D numbers extended consistent fuzzy preference relations

Deng, Xinyang; Lu, Xi; Chan, Felix T. S.; Sadiq, Rehan; Mahadevan, Sankaran; Deng, Yong

doi:10.1016/j.knosys.2014.09.007

Cited by 57 publications

(36 citation statements)

References 77 publications

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“…Step 6: Combine the modified pieces of evidence to generate the evaluation results of the transformer health condition by using Equations (24) and (25).…”

Section: Procedures For Transformer Condition Assessmentmentioning

confidence: 99%

“…Therefore, this limits the actual application of evidence theory, especially the application in the health condition assessment of transformers, including five intersection grades (health, sub-health, minor defect, major defect and critical defect) based on human judgment [25,26]. Unfortunately, little attention has been paid to the rigorous mathematical definition of evidence theory.…”

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confidence: 99%

“…Similarly, subjective and objective weight can be considered as two participants of a game, and the comprehensive weight is the result of the 'weight' game [23]. D numbers, a novel theory initially proposed by Deng [24], has become a powerful method to deal with the uncertainty in actual engineering applications due to its capacity of avoiding the mutually-exclusive hypothesis of the frame of discernment [25,26,33,34].…”

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confidence: 99%

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An Integrated Decision-Making Model for Transformer Condition Assessment Using Game Theory and Modified Evidence Combination Extended by D Numbers

et al. 2016

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Abstract:The power transformer is one of the most critical and expensive components for the stable operation of the power system. Hence, how to obtain the health condition of transformer is of great importance for power utilities. Multi-attribute decision-making (MADM), due to its ability of solving multi-source information problems, has become a quite effective tool to evaluate the health condition of transformers. Currently, the analytic hierarchy process (AHP) and Dempster-Shafer theory are two popular methods to solve MADM problems; however, these techniques rarely consider one-sidedness of the single weighting method and the exclusiveness hypothesis of the Dempster-Shafer theory. To overcome these limitations, this paper introduces a novel decision-making model, which integrates the merits of fuzzy set theory, game theory and modified evidence combination extended by D numbers, to evaluate the health condition of transformers. A four-level framework, which includes three factors and seventeen sub-factors, is put forward to facilitate the evaluation model. The model points out the following: First, the fuzzy set theory is employed to obtain the original basic probability assignments for all indices. Second, the subjective and objective weights of indices, which are calculated by fuzzy AHP and entropy weight, respectively, are integrated to generate the comprehensive weights based on game theory. Finally, based on the above two steps, the modified evidence combination extended by D numbers, which avoids the limitation of the exclusiveness hypothesis in the application of Dempster-Shafer theory, is proposed to obtain the final assessment results of transformers. Case studies are given to demonstrate the proposed modeling process. The results show the effectiveness and engineering practicability of the model in transformer condition assessment.

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“…Step 6: Combine the modified pieces of evidence to generate the evaluation results of the transformer health condition by using Equations (24) and (25).…”

Section: Procedures For Transformer Condition Assessmentmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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An Integrated Decision-Making Model for Transformer Condition Assessment Using Game Theory and Modified Evidence Combination Extended by D Numbers

et al. 2016

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“…The CFPR methodology requires less time, has computational simplicity, and also guarantees consistency of decision matrices. However, as CFPR is based on complete and certain information, there always exists a possible inconsistency risk due to the inability of DMs to deal with overcomplicated objects [34].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid MCDM Technique for Risk Management in Construction Projects

et al. 2018

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Multi-stakeholder based construction projects are subject to potential risk factors due to dynamic business environment and stakeholders' lack of knowledge. When solving project management tasks, it is necessary to quantify the main risk indicators of the projects. Managing these requires suitable risk mitigation strategies to evaluate and analyse their severity. The existence of information asymmetry also causes difficulties with achieving Pareto efficiency. Hence, to ensure balanced satisfaction of all participants, risk evaluation of these projects can be considered as an important part of the multi-criteria decision-making (MCDM) process. In real-life problems, evaluation of project risks is often uncertain and even incomplete, and the prevailing methodologies fail to handle such situations. To address the problem, this paper extends the analytical network process (ANP) methodology in the D numbers domain to handle three types of ambiguous information's, viz. complete, uncertain, and incomplete, and assesses the weight of risk criteria. The D numbers based approach overcomes the deficiencies of the exclusiveness hypothesis and completeness constraint of Dempster-Shafer (D-S) theory. Here, preference ratings of the decision matrix for each decision-maker are determined using a D numbers extended consistent fuzzy preference relation (D-CFPR). An extended multi-attributive border approximation area comparison (MABAC) method in D numbers is then developed to rank and select the best alternative risk response strategy. Finally, an illustrative example from construction sector is presented to check the feasibility of the proposed approach. For checking the reliability of alternative ranking, a comparative analysis is performed with different MCDM approaches in D numbers domain. Based on different criteria weights, a sensitivity analysis of obtained ranking of the hybrid D-ANP-MABAC model is performed to verify the robustness of the proposed method.

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“…One is that how to represent uncertain factors and another is how to fuse these uncertain factors. Many methods are applied to reveal uncertainty factors such as fuzzy set method [17], rough set method [18], probability method [19] [20] and interval numbers [21] [22]. The interval number is an effective way to solve the problem of uncertainty since its value range is bigger than real number, and that has simple forms.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Attribute Decision Making for Investment Decision Based on D Numbers Methods

Zuo¹,

Qin²,

Tian³

et al. 2016

APM

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Investment decision is a traditional multi-attribute decision making (MADM) problem since it has many uncertainty factors and incomplete information such as investment value, cost, sales, etc. D numbers theory is a useful tool to deal with uncertainty factors and incomplete information. In this paper, interval number and D numbers theory are revealed in the uncertain factor and incomplete information of investment decision. The weights of uncertain factors are calculated using entropy weight method. Thus, a new MADM model for investment decision based on D numbers theory is proposed. Numerical example is used to illustrate the efficiency of the proposed method.

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D-CFPR: D numbers extended consistent fuzzy preference relations

Cited by 57 publications

References 77 publications

An Integrated Decision-Making Model for Transformer Condition Assessment Using Game Theory and Modified Evidence Combination Extended by D Numbers

An Integrated Decision-Making Model for Transformer Condition Assessment Using Game Theory and Modified Evidence Combination Extended by D Numbers

A Hybrid MCDM Technique for Risk Management in Construction Projects

A Multi-Attribute Decision Making for Investment Decision Based on D Numbers Methods

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