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Article
Publication date: 2 November 2015

Si-feng Liu, Yingjie Yang, Zhi-geng Fang and Naiming Xie

The purpose of this paper is to present two novel grey cluster evaluation models to solve the difficulty in extending the bounds of each clustering index of grey cluster…

Abstract

Purpose

The purpose of this paper is to present two novel grey cluster evaluation models to solve the difficulty in extending the bounds of each clustering index of grey cluster evaluation models.

Design/methodology/approach

In this paper, the triangular whitenization weight function corresponding to class 1 is changed to a whitenization weight function of its lower measures, and the triangular whitenization weight function corresponding to class s is changed to a whitenization weight function of its upper measures. The difficulty in extending the bound of each clustering indicator is solved with this improvement.

Findings

The findings of this paper are the novel grey cluster evaluation models based on mixed centre-point triangular whitenization weight functions and the novel grey cluster evaluation models based on mixed end-point triangular whitenization weight functions.

Practical implications

A practical evaluation and decision problem for some projects in a university has been studied using the new triangular whitenization weight function.

Originality/value

Particularly, compared with grey variable weight clustering model and grey fixed weight clustering model, the grey cluster evaluation model using whitenization weight function is more suitable to be used to solve the problem of poor information clustering evaluation. The grey cluster evaluation model using endpoint triangular whitenization weight functions is suitable for the situation that all grey boundary is clear, but the most likely points belonging to each grey class are unknown; the grey cluster evaluation model using centre-point triangular whitenization weight functions is suitable for those problems where it is easier to judge the most likely points belonging to each grey class, but the grey boundary is not clear.

Details

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

Keywords

Article
Publication date: 7 August 2017

Jing Ye and Yaoguo Dang

Nowadays, evaluation objects are becoming more and more complicated. The interval grey numbers can be used to more accurately express the evaluation objects. However, the…

Abstract

Purpose

Nowadays, evaluation objects are becoming more and more complicated. The interval grey numbers can be used to more accurately express the evaluation objects. However, the information distribution of interval grey numbers is not balanced. The purpose of this paper is to introduce the central-point triangular whitenization weight function to solve the clustering process of this kind of numbers.

Design/methodology/approach

A new expression of the central-point triangular whitenization weight function is presented in this paper, in terms of the grey cluster problem based on interval grey numbers. By establishing the integral mean value function on the set of interval grey numbers, the application range of grey clustering model is extended to the interval grey number category, and, in this way, the grey fixed weight cluster model based on interval grey numbers is obtained.

Findings

The model is verified by a case which reveals a high distinguishability, validity and practicability.

Practical implications

This model can be used in many fields, such as agriculture, economy, geology and medical science, and provides a feasible method for evaluation schemes in performance evaluation, scheme selection, risk evaluation and so on.

Originality/value

The central-point triangular whitenization weight function is introduced. The method reflects the thought “make full use of the information” in grey system theory and further enriches the system of grey clustering theory as well as expands the application scope of the grey clustering method.

Details

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

Keywords

Article
Publication date: 22 January 2019

Kejia Chen, Ping Chen, Lixi Yang and Lian Jin

The purpose of this paper is to propose a grey clustering evaluation model based on analytic hierarchy process (AHP) and interval grey number (IGN) to solve the clustering…

Abstract

Purpose

The purpose of this paper is to propose a grey clustering evaluation model based on analytic hierarchy process (AHP) and interval grey number (IGN) to solve the clustering evaluation problem with IGNs.

Design/methodology/approach

First, the centre-point triangular whitenisation weight function with real numbers is built, and then by using interval mean function, the whitenisation weight function is extended to IGNs. The weights of evaluation indexes are determined by AHP. Finally, this model is used to evaluate the flight safety of a Chinese airline. The results indicate that the model is effective and reasonable.

Findings

When IGN meets certain conditions, the centre-point triangular whitenisation weight function based on IGN is not multiple-cross and it is normative. It provides a certain standard and basis for obtaining the effective evaluation indexes and determining the scientific evaluation of the grey class.

Originality/value

The traditional grey clustering model is extended to the field of IGN. It can make full use of all the information of the IGN, so the result of the evaluation is more objective and reasonable, which provides supports for solving practical problems.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 12 no. 1
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 2 November 2015

Jun Guo, Xi Zhao and Yimin Huang

The purpose of this paper is to establish a grey clustering evaluation model based on center-point triangular whitenization weight function to evaluate the situation of urban…

Abstract

Purpose

The purpose of this paper is to establish a grey clustering evaluation model based on center-point triangular whitenization weight function to evaluate the situation of urban low-carbon transport development (LTD). The study results intend to provide some theoretical basis and tool support for transport management departments and related researchers who are engaged in low-carbon transport (LT).

Design/methodology/approach

The study uses analytical hierarchy process based on expert investigations to determine the weight of each criteria, classifies the grey clusters based on center-point triangular whitenization weight function, calculates the membership of each development criteria and ranks the development level of all dimensions.

Findings

The research results of case city show that low-carbon technology is in “poor” level, transport facility is in “superior” level, low-carbon policy and environmental coordination is in “intermediate” level, transport management is in “good” level and the overall LTD level is in “intermediate” level.

Practical implications

Reducing the carbon emissions of urban transport and achieving LT is the key to promote urban sustainable development, the scientific judgment of transport development situation is the premise of promoting LTD. Therefore, based on the practices of LT in China, the study systematically clarifies LTD from five dimensions of reflecting LTD.

Originality/value

From the perspective of sustainable development, the evaluation index system of LTD is built with five dimensions consisting of low-carbon technology, low-carbon policy, transport facility, transport management and environmental coordination. Then assess the LTD by using the grey clustering evaluation model based on center-point triangular whitenization weight. This paper presents a new research idea for LTD evaluation.

Details

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

Keywords

Article
Publication date: 28 October 2014

Tianbo Li, Ershi Qi and Yimin Huang

The purpose of this paper is to attempt to establish a grey clustering evaluation model of center-point triangular whitenization weight function to measure the performance of…

Abstract

Purpose

The purpose of this paper is to attempt to establish a grey clustering evaluation model of center-point triangular whitenization weight function to measure the performance of enterprise's management innovation (MI). The author intends to provide some theory basis and tool support for enterprise's managers and other researchers who are engaged in performance measuring.

Design/methodology/approach

The study uses questionnaire survey and expert interviews to determine the index weight of enterprise's MI performance (MIP), classifies the grey clusters based on center-point triangular whitenization weight function, calculates the membership of performance criteria and ranks the performance level of all dimensions.

Findings

The survey data of case company shows that production performance is in superior level, employee and society influence performance are in satisfied level, finance and market performance are in intermediate level, total MIP is in satisfied level.

Practical implications

MI is the fundamental way to keep enterprise's core competitiveness and achieve its strategic objectives. Performance is an effective tool to measure the MI. Therefore, based on the practices of MI in China, the study systematically clarifies the performance level of MI from five dimensions.

Originality/value

The evaluation index of enterprise's MIP is built with five dimensions which contain production, market, finance, employee and social influence. The grey clustering evaluation model based on triangular whitenization weight function is applied to assess the performance criteria. This paper presents a new research idea for enterprise's performance evaluation.

Details

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

Keywords

Article
Publication date: 2 March 2015

Hamed Maleki and Mohammad Taghi Taghavi Fard

The time required for a certain task to be performed normally reduces on its frequent completion, as more units are produced over time, it is expected to have an increase in the…

Abstract

Purpose

The time required for a certain task to be performed normally reduces on its frequent completion, as more units are produced over time, it is expected to have an increase in the total worker’s output performance. Learning curve (LC) is a mathematical representation to estimate the time of tasks which occurs repeatedly. The parameter prediction is considered a major disadvantage from which LC suffers. The purpose of this paper is to investigate grey systems theory as a method for the standard time.

Design/methodology/approach

The proposed method starts with data which are obtained by traditional time study and then, models LC for an assembling activity of Electrogen Company. The paper studies the grey evaluation method based on triangular whitenization weight functions which includes two classes: endpoint triangular whitenization functions and center-point triangular whitenization functions. The grey system results are compared with those of the LC.

Findings

The results show that the standard time given by grey systems theory is closer than the standard time given by LC to standard time with 100 per cent performance level.

Originality/value

Scheduling problems are complex and uncertain, and it is very rare for such systems to be exactly determined in all their complexity. According to grey systems theory, the job processing time can be considered as the object that extension is definite but intension is uncertain. Consequently, grey systems theory with its focus on the uncertainty problems of small samples and incomplete information is proposed in the paper.

Details

Journal of Manufacturing Technology Management, vol. 26 no. 2
Type: Research Article
ISSN: 1741-038X

Keywords

Article
Publication date: 28 January 2014

Yu Zhang, Jie Ni, Jian Liu and Li-rong Jian

– This paper aims to investigate the performance of Jiangsu Province industrial technology innovation strategy alliance.

238

Abstract

Purpose

This paper aims to investigate the performance of Jiangsu Province industrial technology innovation strategy alliance.

Design/methodology/approach

Through a preliminary investigation of 30 Jiangsu industrial technology innovation strategic alliances, this paper analyzed the status and extracted 18 alliances to conduct an in-depth investigation. By grey evaluation method based on center-point triangular whitenization weight function, the paper classified and analyzed alliances.

Findings

The results show that university or research institutions-oriented alliance perform better, but the government/enterprise-oriented alliance perform diverse, and majority is rated “general”.

Originality/value

The paper succeeds in clustering analysis to Jiangsu Province industrial technology innovation strategy alliance with insufficient data. And according to the result of clustering, it analyzes the causes, which provide value information for the sustainable development of Jiangsu Province industrial technology innovation strategy alliance.

Details

Grey Systems: Theory and Application, vol. 4 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 6 February 2017

Hamed Maleki and Yingjie Yang

The purpose of this paper is to illustrate an uncertain programming model for scheduling of preventive maintenance (PM) actions. The PM scheduling, in which PM actions are…

Abstract

Purpose

The purpose of this paper is to illustrate an uncertain programming model for scheduling of preventive maintenance (PM) actions. The PM scheduling, in which PM actions are performed under fixed intervals, is solved by grey systems theory.

Design/methodology/approach

The paper applied the grey evaluation method based on triangular whitenization weight functions which includes two classes: endpoint evaluation method and center-point evaluation method.

Findings

Two methods give the same results based on endpoint and center-point triangular whitenization weight functions. For validation, the results were compared by Cassady’s method.

Originality/value

The scheduling of PM is crucial in reliability and maintenance engineering. Hundreds of parts compose complex machines that require replacement and/or repairing. It is helpful to reduce the outage loss on frequent repair/replacement parts and avoid lack of maintenance of the equipment by controlling the equipment maintenance frequency.

Details

Grey Systems: Theory and Application, vol. 7 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 6 November 2019

Dang Luo and Zhang Huihui

The purpose of this paper is to propose a grey clustering model based on kernel and information field to deal with the situation in which both the observation values and the…

Abstract

Purpose

The purpose of this paper is to propose a grey clustering model based on kernel and information field to deal with the situation in which both the observation values and the turning points of the whitenization weight function are interval grey numbers.

Design/methodology/approach

First, the “unreduced axiom of degree of greyness” was expanded to obtain the inference of “information field not-reducing”. Then, based on the theoretical basis of inference, the expression of whitenization weight function with interval grey number was provided. The grey clustering model and fuzzy clustering model were compared to analyse the relationship and difference between the two models. Finally, the paper model and the fuzzy clustering model were applied to the example analysis, and the interval grey number clustering model was established to analyse the influencing factors of regional drought disaster risk in Henan Province.

Findings

The example analysis results illustrate that although the two clustering methods have different theoretical basis, they are suitable for dealing with complex systems with uncertainty or grey characteristic, solving the problem of incomplete system information, which has certain feasibility and rationality. The clustering results of case study show that five influencing factors of regional drought disaster risk in Henan Province are divided into three classes, consistent with the actual situation, and they show the validity and practicability of the clustering model.

Originality/value

The paper proposes a new whitenization weight function with interval grey number that can transform interval grey number operations into real number operations. It not only simplifies the calculation steps, but it has a great significance for the “small data sets and poor information” grey system and has a universal applicability.

Details

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

Keywords

Article
Publication date: 1 February 2016

Sifeng Liu, Yingjie Yang, Naiming Xie and Jeffrey Forrest

The purpose of this paper is to summarize the progress in grey system research during 2000-2015, so as to present some important new concepts, models, methods and a new framework…

1802

Abstract

Purpose

The purpose of this paper is to summarize the progress in grey system research during 2000-2015, so as to present some important new concepts, models, methods and a new framework of grey system theory.

Design/methodology/approach

The new thinking, new models and new methods of grey system theory and their applications are presented in this paper. It includes algorithm rules of grey numbers based on the “kernel” and the degree of greyness of grey numbers, the concept of general grey numbers, the synthesis axiom of degree of greyness of grey numbers and their operations; the general form of buffer operators of grey sequence operators; the four basic models of grey model GM(1,1), such as even GM, original difference GM, even difference GM, discrete GM and the suitable sequence type of each basic model, and suitable range of most used grey forecasting models; the similarity degree of grey incidences, the closeness degree of grey incidences and the three-dimensional absolute degree of grey incidence of grey incidence analysis models; the grey cluster model based on center-point and end-point mixed triangular whitenization functions; the multi-attribute intelligent grey target decision model, the two stages decision model with grey synthetic measure of grey decision models; grey game models, grey input-output models of grey combined models; and the problems of robust stability for grey stochastic time-delay systems of neutral type, distributed-delay type and neutral distributed-delay type of grey control, etc. And the new framework of grey system theory is given as well.

Findings

The problems which remain for further studying are discussed at the end of each section. The reader could know the general picture of research and developing trend of grey system theory from this paper.

Practical implications

A lot of successful practical applications of the new models to solve various problems have been found in many different areas of natural science, social science and engineering, including spaceflight, civil aviation, information, metallurgy, machinery, petroleum, chemical industry, electrical power, electronics, light industries, energy resources, transportation, medicine, health, agriculture, forestry, geography, hydrology, seismology, meteorology, environment protection, architecture, behavioral science, management science, law, education, military science, etc. These practical applications have brought forward definite and noticeable social and economic benefits. It demonstrates a wide range of applicability of grey system theory, especially in the situation where the available information is incomplete and the collected data are inaccurate.

Originality/value

The reader is given a general picture of grey systems theory as a new model system and a new framework for studying problems where partial information is known; especially for uncertain systems with few data points and poor information. The problems remaining for further studying are identified at the end of each section.

Details

Grey Systems: Theory and Application, vol. 6 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

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