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Article
Publication date: 8 January 2018

Peng Li and Cuiping Wei

In multi-criteria decision-making with interval grey number information, decision makers usually take a risk to rank or choose some very similar alternatives…

Abstract

Purpose

In multi-criteria decision-making with interval grey number information, decision makers usually take a risk to rank or choose some very similar alternatives. Additionally, when evaluating only one alternative, decision makers can only obtain a specific value using traditional decision-making methods and may find it hard to cluster the alternatives to the “correct class” because these methods lack predetermined reference points. To overcome this problem, this paper aims to propose a two-stage grey decision-making method.

Design/methodology/approach

First, a new type of clustering method for interval grey numbers is designed by proposing a new possibility function for grey numbers. Based on this clustering method, a new grey clustering evaluation model for interval grey numbers is proposed by which decision makers can obtain the grade rating information of each alternative. Then, according to the grey clustering evaluation model, a new two-stage decision-making method is introduced to solve the problem that some alternatives are very similar by designing a grey comprehensive decision coefficient of alternatives.

Findings

The authors propose a new grey clustering evaluation model to deal with interval grey numbers. They design a new model to obtain the membership degree for the interval grey numbers and then propose a new grey clustering evaluation model, which can evaluate only one alternative by predefined grey classes. Then, by the grey comprehensive decision coefficient, a two-stage grey evaluation decision-making method is put forward to solve the problem that some alternatives are very close and hard to be distinguished.

Originality/value

A new grey clustering evaluation model is proposed, which can evaluate only one alternative by predefined grey classes. A two-stage grey evaluation decision-making method is given to solve the problem that some alternatives are very close and hard to be distinguished.

Details

Kybernetes, vol. 47 no. 4
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 26 February 2021

Baohua Yang, Junming Jiang and Jinshuai Zhao

The purpose of this study is to construct a gray relational model based on information diffusion to avoid rank reversal when the available decision information is…

Abstract

Purpose

The purpose of this study is to construct a gray relational model based on information diffusion to avoid rank reversal when the available decision information is insufficient, or the decision objects vary.

Design/methodology/approach

Considering that the sample dependence of the ideal sequence selection in gray relational decision-making is based on case sampling, which causes the phenomenon of rank reversal, this study designs an ideal point diffusion method based on the development trend and distribution skewness of the sample information. In this method, a gray relational model for sample classification is constructed using a virtual-ideal sequence. Subsequently, an optimization model is established to obtain the criteria weights and classification radius values that minimize the deviation between the comprehensive relational degree of the classification object and the critical value.

Findings

The rank-reversal problem in gray relational models could drive decision-makers away from using this method. The results of this study demonstrate that the proposed gray relational model based on information diffusion and virtual-ideal sequencing can effectively avoid rank reversal. The method is applied to classify 31 brownfield redevelopment projects based on available interval gray information. The case analysis verifies the rationality and feasibility of the model.

Originality/value

This study proposes a robust method for ideal point choice when the decision information is limited or dynamic. This method can reduce the influence of ideal sequence changes in gray relational models on decision-making results considerably better than other approaches.

Details

Grey Systems: Theory and Application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2043-9377

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Article
Publication date: 23 September 2019

Bingjun Li and Xiaoxiao Zhu

The purpose of this paper is to put forward the grey relational decision-making model of three-parameter interval grey number based on Analytic Hierarchy Process (AHP) and…

Abstract

Purpose

The purpose of this paper is to put forward the grey relational decision-making model of three-parameter interval grey number based on Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA), based on the previous study of grey relational decision-making model, and it considers the advantages of the decision-making schemes and the subjective preferences of decision makers.

Design/methodology/approach

First of all, through AHP, the preference of each index is analyzed and the index weight is determined. Second, the DEA model is adopted to obtain the index weight from the perspective of the most beneficial to each scheme and objectively reflect the advantages of different schemes. Then, assign the comprehensive weights to each index of the grey relational decision-making model of three-parameter interval grey number, and calculate the grey relation degree of each scheme to rank the schemes.

Findings

The effectiveness of the model is proved by an example of carrier aircraft selection.

Practical implications

The applicability of this model is analyzed by taking carrier aircraft selection as an example. In fact, this model can also be widely used in agriculture, industry, economy, society and other fields.

Originality/value

In this paper, the combination of AHP and DEA is used to determine the index weight. Based on which, the grey relation degree under the three-parameter interval grey number is calculated. It intended the application space of the grey relational decision-making model.

Details

Grey Systems: Theory and Application, vol. 10 no. 1
Type: Research Article
ISSN: 2043-9377

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Article
Publication date: 28 October 2014

Yong Liu, Wu-yong Qian and Jeffrey Forrest

– The purpose of this paper is to construct a novel grey dominance variable precision rough model.

Abstract

Purpose

The purpose of this paper is to construct a novel grey dominance variable precision rough model.

Design/methodology/approach

To deal with the problems that the attribute values of the decision-making object are often not exact numbers but interval grey numbers, and the decision-making attributes satisfy a certain preference relationship in the decision-making information because of the complexity and uncertainty of the real world, the authors take advantage of the theoretical thinking of the grey systems, dominance rough set theory and variable precision rough set theory, and construct a novel dominance variable precision rough set model. On the basis of the thinking logic of grey systems, the authors first define the concepts of balance degree, dominance degree and inferior degree, and then the grey dominance relationship based on the comparison of interval grey numbers. Then the authors use the grey dominance relationship to substitute for the indiscernibility relationship of the variable precision rough set so that the grey dominance variable precision rough model is naturally utilized to reduce the system's attributes in order to derive the needed decision rules. At the end, the authors use a decision-making example of the radar target selection to demonstrate the feasibility and effectiveness of the novel model.

Findings

The results show that the proposed model possesses certain fault tolerance ability and can well-realize decision rule extraction and knowledge discovery out of a given incomplete information system.

Practical implications

The method exposed in the paper can be used to deal with the decision-making problems with the grey information, preference information and noise data.

Originality/value

The paper succeeds in realizing both the grey decision-making information with preference information and noise data and the extraction of decision-making rules.

Details

Grey Systems: Theory and Application, vol. 4 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

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Article
Publication date: 7 August 2017

Chuanmin Mi, Lin Xiao, Sifeng Liu and Xiaoyan Ruan

With respect to the multiple-attribute decision-making problem with subjective preference for a certain attribute whose weight-value range have been given over other…

Abstract

Purpose

With respect to the multiple-attribute decision-making problem with subjective preference for a certain attribute whose weight-value range have been given over other attributes whose weight values are unknown, a method based on the mean value of the grey number is proposed to analyse the decision-making problem. This method is used to choose a supply-chain partner under the condition that the decision makers have a preference for a certain attribute of various alternatives. The paper aims to discuss these issues.

Design/methodology/approach

First, the middle value of the preferred attribute’s weight-value range is supposed to be its weight value according to the content of the mean value of the grey number. Second, to reflect the decision maker’s subjective preference information, an improved optimisation model that requests the minimum deviation between the actual and expected numerical value of each attribute is constructed to assess the attributes’ weights. Third, the correlated degree and the correlation matrix, which are determined by the weight values of all attributes, are used to rank all the alternatives.

Findings

This paper provides a method for making a decision when decision makers have a preference for a certain attribute from an array of various alternatives, and the range of the certain attribute’s weight value is given but the weight value of the other attributes is unknown. When applied to supply-chain partner selection, this method proves feasible and effective.

Practical implications

This method is feasible and effective when applied to supply-chain partner selection, and can be applied to other kinds of decision-making problems. This means it has significant theoretical importance and extensive practical value.

Originality/value

Based on the mean value of the grey number, an optimisation model is built to determine the importance degree of each attribute, then the correlated degree of each alternative is combined to rank all the alternatives. This method can suit the decision makers’ subjective preference for a certain attribute well.

Details

Grey Systems: Theory and Application, vol. 7 no. 2
Type: Research Article
ISSN: 2043-9377

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Article
Publication date: 29 July 2014

Yong Liu and Huan-huan Zhao

– The purpose of this paper is to construct a dynamic information aggregation decision-making model based on variable precision rough set.

Abstract

Purpose

The purpose of this paper is to construct a dynamic information aggregation decision-making model based on variable precision rough set.

Design/methodology/approach

To deal with the dynamic decision-making problems, the grey relational analysis method, grey fixed weight clustering based on the centre triangle whitening weight function and maximum entropy principle is used to establish the dynamic information aggregation decision-making model based on variable precision rough set. The method, to begin with, the grey relational analysis method is used to determine the attributes weights of each stage; taking the proximity of the attribute measurement value and positive and negative desired effect value and the uncertainty of time weight into account, a multi-objective optimisation model based on maximum entropy principle is established to solve the model with Lagrange multiplier method, so that time weights expression are acquired; what is more, the decision-making attribute is obtained by grey fixed weight clustering based on the centre triangle whitening weight function, so that multi-decision-making table with dynamic characteristics is established, and then probabilistic decision rules from multi-criteria decision table are derived by applying variable precision rough set. Finally, a decision-making model validates the feasibility and effectiveness of the model.

Findings

The results show that it the proposed model can well aggregate the multi-stage dynamic decision-making information, realise the extraction of decision-making rules.

Research limitations/implications

The method exposed in the paper can be used to deal with the decision-making problems with the multi-stage dynamic characteristics, and decision-making attributes contain noise data and the attribute values are interval grey numbers.

Originality/value

The paper succeeds in realising both the aggregation of dynamic decision-making information and the extraction of decision-making rules.

Details

Grey Systems: Theory and Application, vol. 4 no. 2
Type: Research Article
ISSN: 2043-9377

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Article
Publication date: 18 September 2020

Xiao Bai, Yan Xu and Sifeng Liu

The purpose of this paper is to establish the index system of leading industries in Kashgar urban agglomeration, and use the multi-attribute weighted intelligent grey

Abstract

Purpose

The purpose of this paper is to establish the index system of leading industries in Kashgar urban agglomeration, and use the multi-attribute weighted intelligent grey target decision-making evaluation model to measure the comprehensive effect, so as to select the leading industries of Kashgar urban agglomeration.

Design/methodology/approach

First, 18 industries in Kashgar urban agglomerations are taken as objectives, and four indexes, namely, demand income elasticity index, growth rate index, labor productivity growth rate index and contribution rate of output value, are selected to construct an evaluation system for leading industry selection in Kashgar urban agglomerations. Then, grey incidence degree method is used to determine the decision-making power of each decision-making objective. Finally, multi-attribute weighted intelligent grey target decision-making evaluation model is used to measure the comprehensive effect of the objective system of leading industries in Kashgar urban agglomerations.

Findings

It can be seen that the multi-attribute weighted intelligent grey target decision-making evaluation model is more convenient to be used in selecting regional leading industries, and the results are accurate and feasible. Based on the calculation results and the actual economic development requirements of Kashgar urban agglomeration, the leading industries of Kashgar urban agglomeration can be determined as: wood processing, furniture, paper making and printing; wholesale and retail; construction; equipment manufacturing; transportation, storage and postal services.

Originality/value

First, it is a new method in selecting regional leading industry by using the multi-attribute weighted intelligent grey target decision-making evaluation model. Second, since there is relatively little research on Kashgar urban agglomeration, especially on leading industries in Kashgar urban agglomeration. The research in this paper can not only enrich the research on selecting leading industries in urban agglomeration but also provide scientific reference for relevant government agencies to formulate economic development plans.

Details

Grey Systems: Theory and Application, vol. 11 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

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Article
Publication date: 28 May 2021

Zainab Asim, Syed Aqib Aqib Jalil, Shakeel Javaid and Syed Mohd Muneeb

This paper aims to develop a grey decentralized bi-level multi-objective programming (MOP) model. A solution approach is also proposed for the given model. A production…

Abstract

Purpose

This paper aims to develop a grey decentralized bi-level multi-objective programming (MOP) model. A solution approach is also proposed for the given model. A production and transportation plan for a closed loop supply chain network under an uncertain environment and different scenarios is also developed.

Design/methodology/approach

In this paper, we combined grey linear programming (GLP) and fuzzy set theory to present a solution approach for the problem. The proposed model first solves the given problem using GLP. Membership functions for the decision variables under the control of the leader and for the goals are created. These membership functions are then used to generate the final solutions.

Findings

This paper provides insight for fomenting the decision-making process while providing a more flexible approach in uncertain logistics problems. The deviations of the final solution from the individual best solutions of the two levels are very little. These deviations can further be reduced by adjusting the tolerances associated with the decision variables under the control of the leader.

Practical implications

The proposed approach uses the concept of membership functions of linear form, and thus, requires less computational efforts while providing effective results. Most of the organizations exhibit decentralized decision-making under the presence of uncertainties. Therefore, the present study is helpful in dealing with such scenarios.

Originality/value

This is the first time, formulation of a decentralized bi-level multi-objective model under a grey environment is carried out as per the best knowledge of the authors. A solution approach is developed for bi-level MOP under grey uncertainty.

Details

Journal of Modelling in Management, vol. 16 no. 3
Type: Research Article
ISSN: 1746-5664

Keywords

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Article
Publication date: 19 March 2021

Junliang Du, Sifeng Liu and Yong Liu

The purpose of this paper is to advance a novel grey variable dual precision rough set model for grey concept.

Abstract

Purpose

The purpose of this paper is to advance a novel grey variable dual precision rough set model for grey concept.

Design/methodology/approach

To obtain the approximation of a grey object, the authors first define the concepts of grey rough membership degree and grey degree of approximation on the basic thinking logic of variable precision rough set. Based on grey rough membership degree and grey degree of approximation, the authors proposed a grey variable dual precision rough set model. It uses a clear knowledge concept to approximate a grey concept, and the output result is also a clear concept.

Findings

The result demonstrates that the proposed model may be closer to the actual decision-making situation, can effectively improve the rationality and scientificity of the approximation and reduce the risk of decision-making. It can effectively achieve the whitenization of grey objects. The model can be degenerated to traditional variable precision rough fuzzy set model, variable precision rough set model and classic Pawlak rough set, when some specific conditions are met.

Practical implications

The method exposed in the paper can be used to solve multi-criteria decision problems with grey decision objects and provide a decision rule. It can also help us better realize knowledge discovery and attribute reduction. It can effectively achieve the whitenization of grey object.

Originality/value

This method proposed in this paper implements a rough approximation of grey decision object and obtains low-risk probabilistic decision rule. It can effectively achieve a certain degree of whitenization of some grey objects.

Details

Grey Systems: Theory and Application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2043-9377

Keywords

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Article
Publication date: 2 November 2015

Qiuping Wang, Subing Liu and Guoqiang Xiong

The aggregation of information from a group of decision experts for developing collective opinion is the important question in practice. The purpose of this paper is to…

Abstract

Purpose

The aggregation of information from a group of decision experts for developing collective opinion is the important question in practice. The purpose of this paper is to provide a group decision-making method via ordered weighted aggregation (OWA) operator and grey incidence analysis.

Design/methodology/approach

In this study, OWA operator provides aggregation of attribute values to form an overall decision for each decision expert, and grey incidence model provides aggregation of decision experts’ evaluations to form overall score for each alternative. The example illustrates the procedure and practicability of the proposed model.

Findings

A new thought for multiple attribute group decision-making problems is given. The proposed method produces an overall desirability score for each alternative.

Practical implications

This is to obtain a more comprehensive and realistic solution to the given group decision-making problem. The proposed analysis method of group decision-making problems reveals vitality of grey systems theory.

Originality/value

This paper combines OWA operator and grey incidence analysis to obtain a novel and effective method for group decision making. It is suitable for group decision-making problems in which the attribute weights are completely unknown, expert weights are completely unknown.

Details

Grey Systems: Theory and Application, vol. 5 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

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