An Improvement to Determining Expert Weights in Group Multiple Attribute Decision Making Problem

Abootalebi, S.; Hadi-Vencheh, A.; Jamshidi, Ali

doi:10.1007/s10726-018-9555-0

Cited by 21 publications

(7 citation statements)

References 1 publication

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“…Also, in the course of multi-attribute group decisionmaking, based on the experts' preference information, the weights of experts can be obtained. In [5], a new linear programming model is proposed to find the optimal expert weights based on deviation function. In [16], an entropybased approach is proposed to determine the weights of experts by defining a projection measure for the hybrid information representations.…”

Section: E Preference Information In Magdmmentioning

confidence: 99%

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A Neural Network-Based Approach to Multi-Attribute Group Decision-Making with Heterogeneous Preference Information

Zhang

et al. 2022

Scientific Programming

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For the problem of multi-attribute group decision-making with heterogeneous preference information on attribute values and overall preference orderings on alternatives, this article proposes a neural network-based approach. In the approach, firstly, the heterogeneous preference information on attribute values and overall preference orderings on alternatives are normalized. Secondly, based on the normalization results, two optimization models are set up to determine attribute weights and expert weights, respectively. Thirdly, two neural networks are set up and trained to determine attribute weights and expert weights based on the optimization models. Then, the overall values of the alternatives are obtained as well as their rankings. Simulations on the proposed neural networks are conducted for illustrations.

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Section: E Preference Information In Magdmmentioning

confidence: 99%

“…In the course of multi-attribute decision-making, a group of experts is always invited to take part in the voting work [1][2][3][4][5]. For some complex multi-attribute decision-making problems, for example, the international joint project selections across di erent countries, the experts may come from di erent countries.…”

Section: Introductionmentioning

confidence: 99%

A Neural Network-Based Approach to Multi-Attribute Group Decision-Making with Heterogeneous Preference Information

Zhang

et al. 2022

Scientific Programming

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“…Calculate the difference weights of attributes. Compute the distance between all alternatives under attribute c k j and obtain the difference weight ω k ‴ j using equations (13) and (14).…”

Section: Proposed Algorithmsmentioning

confidence: 99%

“…Cheng et al [12] studied expert weights from incomplete linguistic preference relations based on uniform consistency. Abootalebi et al [13] proposed a linear programming model based on a deviation function to find the optimal expert weights.…”

Section: Introductionmentioning

confidence: 99%

Weight Analysis for Multiattribute Group Decision-Making with Interval Grey Numbers Based on Decision-Makers’ Psychological Criteria

Guo

Liu

Yang

2020

Mathematical Problems in Engineering

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To address the problem of multiattribute group decision-making with interval grey numbers, decision matrices are adjusted using kernels of interval grey numbers to reduce the psychological effects of decision-makers. The comprehensive weights of attributes are obtained by aggregating the subjective weights with objective weights, which are calculated based on the accuracy and difference of attributes. Considering the consistent, best, and worst decision-making abilities of decision-makers, grey incidence models are established to obtain the consistency weights and individual bipolar weights of decision-makers; then, the comprehensive weights of decision-makers are determined. A clustering approach of interval grey numbers is presented, and overall evaluations are obtained. Finally, an example is provided and its validity is tested to verify the feasibility of the proposed method.

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“…Xu and Cai [18] established a nonlinear programming model to determine the experts' weights based on the principle that the experts' weights should produce the highest consistency of the experts. On this basis, the authors of [19] pointed out the shortcomings of applying genetic algorithm to solve the nonlinear programming model and proposed a new method to determine the experts' weights by linearizing the nonlinear programming model. e authors of [20] proposed the concept of probabilistic uncertain linguistic term sets and the method for probabilistic uncertain linguistic multiattribute group decision-making problems.…”

Section: Literature Reviewmentioning

confidence: 99%

A Competitive Multiattribute Group Decision-Making Approach for the Game between Manufacturers

Zhang

Jiang

Yan

et al. 2019

Computational Intelligence and Neuroscience

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Under the competitive market environment, the game between manufacturers comes down to the competitive multiattribute group decision-making problem. In this study, the evaluation information of experts is given in the form of 2-dimension 2-tuple linguistic variables, and an approach is proposed for the competitive multiattribute group decision-making problem based on game theory and evidence theory. Firstly, based on the evidence theory, the attribute values of each situation are obtained by aggregating the 2-dimension 2-tuple linguistic evaluation information given by experts. Secondly, according to the attribute values of every situation, the evidence theory is applied for the second aggregation to obtain the overall values of every situation, and then the game matrix of competitive multiattribute group decision problem is formed. Then, according to the bivariate game matrix, the Nash equilibrium point of competitive multiattribute group decision-making problem is determined based on game theory. Finally, a practical case about the alternative selections for a duopoly problem is used to illustrate the effectiveness and applicability of the proposed approach for the competitive multiattribute group decision-making problem.

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An Improvement to Determining Expert Weights in Group Multiple Attribute Decision Making Problem

Cited by 21 publications

References 1 publication

A Neural Network-Based Approach to Multi-Attribute Group Decision-Making with Heterogeneous Preference Information

A Neural Network-Based Approach to Multi-Attribute Group Decision-Making with Heterogeneous Preference Information

Weight Analysis for Multiattribute Group Decision-Making with Interval Grey Numbers Based on Decision-Makers’ Psychological Criteria

A Competitive Multiattribute Group Decision-Making Approach for the Game between Manufacturers

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