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Article
Publication date: 10 July 2007

Guo‐Dong Li, Daisuke Yamaguchi and Masatake Nagai

This paper aims to resolve the uncertain problem in suppliers selection chain management system through using the proposed multiple attribute decision‐making (MADM) approach.

Abstract

Purpose

This paper aims to resolve the uncertain problem in suppliers selection chain management system through using the proposed multiple attribute decision‐making (MADM) approach.

Design/methodology/approach

The approach which combines grey system theory with rough set theory is proposed.

Findings

This proposed approach take advantage of mathematical analysis power of grey system theory and at the same time take advantage of data mining and knowledge discovery power of rough set theory. It will be suitable to decision making under a more uncertain environment.

Originality/value

Provides a viewpoint on the attribute values and attribute weights of rough set decision table for all alternatives are decided by grey number based on grey system theory. The best ideal supplier can be decided by grey relational analysis based on grey number.

Details

Journal of Modelling in Management, vol. 2 no. 2
Type: Research Article
ISSN: 1746-5664

Keywords

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Article
Publication date: 28 October 2014

Om Ji Shukla, Gunjan Soni and G. Anand

In the current customer-driven market, the manufacturers have to be highly responsive and flexible to deliver a variety of products. Hence, to meet this dynamic and…

Abstract

Purpose

In the current customer-driven market, the manufacturers have to be highly responsive and flexible to deliver a variety of products. Hence, to meet this dynamic and uncertain market changes, the production system, which enables the manufacturing of such variety of products should be able to meet such diverse, dynamic changes. Hence, selecting a suitable manufacturing system is a key strategic decision for today's manufacturing organization, which needs to survive in these uncertain market conditions. Hence, the purpose of this paper is to present a decision-making model for selecting the best manufacturing system and also discuss the criteria on the basis of which the management can select the same.

Design/methodology/approach

A case of small- and medium-sized company is presented, in which the management is deciding to establish a most suitable manufacturing system. To supplement this, a suitable multi-criteria decision-making model (MCDM), the grey approach is used to analyze manufacturing system alternatives based on various decision criteria to arrive a comparative ranking.

Findings

An extensive analysis of grey-based decision-making model described grey decision matrix, grey normalized decision matrix, grey weighted normalized decision matrix and grey possibility degrees for three alternatives revealed that lean manufacturing systems was found to be the most suitable manufacturing system among three alternatives for a given case.

Research limitations/implications

The same study can be extended by including sub-criteria with main criteria for selection of manufacturing system by utilizing two MCDM techniques such as AHP or ANP with Grey approach.

Practical implications

The Grey approach has been discussed in a detailed way and it will be useful for the managers to use this approach as a tool for solving similar type of decision-making problems in their organizations in the future.

Originality/value

Although, the problem of selecting a suitable manufacturing system is often addressed both in practice and research, very few reports are available in the literature of Grey-based decision models that demonstrated its application for selecting a suitable manufacturing systems.

Details

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

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Article
Publication date: 17 August 2012

Sifeng Liu, Jeffrey Forrest and Yingjie Yang

The purpose of this paper is to introduce the elementary concepts and fundamental principles of grey systems and the main components of grey systems theory. Also to…

Abstract

Purpose

The purpose of this paper is to introduce the elementary concepts and fundamental principles of grey systems and the main components of grey systems theory. Also to discuss the astonishing progress that grey systems theory has made in the world of learning and its wide‐ranging applications in the entire spectrum of science.

Design/methodology/approach

The characteristics of unascertained systems including incomplete information and inaccuracies in data are analysed and four uncertain theories: probability statistics, fuzzy mathematics, grey system and rough set theory are compared. The scientific principle of simplicity and how precise models suffer from inaccuracies are also shown.

Findings

The four uncertain theories, probability statistics, fuzzy mathematics, grey system and rough set theory are examined with different research objects, different basic sets, different methods and procedures, different data requirements, different emphasis, different objectives and different characteristics.

Practical implications

The scientific principle of simplicity and how precise models suffer from inaccuracies are shown. So, precise models are not necessarily an effective means to deal with complex matters, especially in the case that the available information is incomplete and the collected data inaccurate.

Originality/value

The elementary concepts and fundamental principles of grey systems and the main components of grey systems theory are introduced briefly. The reader is given a general picture of grey systems theory as a new method for studying problems where partial information is known, partial information is unknown; especially for uncertain systems with few data points and poor information.

Details

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

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Article
Publication date: 7 August 2009

Sifeng Liu, Jeffrey Forrest and Robert Vallee

The purpose of this paper is to present the scientific background from which grey systems theory came into being, the astonishing progress that grey systems theory has…

Abstract

Purpose

The purpose of this paper is to present the scientific background from which grey systems theory came into being, the astonishing progress that grey systems theory has made in the world of learning and its wide‐ranging applications in the entire spectrum of science.

Design/methodology/approach

The grey uncertainty is compared with other kinds of uncertainty such as stochastic uncertainty, unascertainty, fuzzy and rough uncertainty.

Findings

The advances in grey systems theory and its various successful applications are introduced individually by algorithms of grey numbers and grey algebraic systems, grey dynamic models and grey predictions, grey optimization analysis for decision making, grey control models.

Research limitations/implications

Many scientific theories require the unremitting efforts of several generations of people and have gone through hundreds of years before reaching maturity and perfection. Grey systems theory is still in its growth period. So, it is unavoidable that there exist immature and imperfect parts in the theory.

Originality/value

Grey systems theory is a new method for studying problems of uncertainty with few data points and poor information. This new theory studies small samples and systems with poor information, which have partial information known, partial information unknown. It describes adequately and monitors effectively systems' operations and evolutions through extracting valuable information from the little known information. Grey systems theory comes into being along with the development of modern systems science and uncertainty systems theories and methods. It is also a result of deepened perceptivity about uncertain systems.

Details

Kybernetes, vol. 38 no. 7/8
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 3 August 2015

Delcea Camelia

As the grey systems theory has been used over the time in different economic areas, in the following, a short literature review will be put forward, starting from the…

Abstract

Purpose

As the grey systems theory has been used over the time in different economic areas, in the following, a short literature review will be put forward, starting from the usage of these theory in the supply chain management, decision-making process, financial performance evaluation, credit risk, energy consumption, investment efficiency, etc. The purpose of this paper is to identify some key studies from all the economic areas in which the grey systems can be used in order to open and to bring to the researchers new domains in which they can manifest their interest and in which they can successfully use the methods offered by the grey systems theory.

Design/methodology/approach

Using the search engine offered by the Web of Science, a literature review has been performed for the economic grey systems applications developed over the time on both economic diagnosis and system’s forecasting. In addition, some hybrid grey systems theory – artificial intelligence techniques models have also been presented.

Findings

The grey systems theory has brought its contribution to numerous economic application from various fields such as: supply chain management, decision-making process, financial performance evaluation, credit risk, energy consumption, investment efficiency, firms’ bankruptcy, product development, consumer income, monetization ratio, etc.

Research limitations/implications

The present paper identifies the some of the most representative examples in which the grey theory has been used, but, in the same time, there are a lot of studies that have not been mentioned here due to the lack of space.

Originality/value

Unlike other review papers written on the grey systems theory area, the present paper is only focusing on the economic applications in which this theory has been successfully used, bringing to the reader a general overview on this field and, in the same time, enabling new research perspectives.

Details

Grey Systems: Theory and Application, vol. 5 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

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Article
Publication date: 3 August 2015

Scarlat Emil and Virginia Mărăcine

The purpose of this paper is to discuss how tacit and explicit knowledge determine grey knowledge and how these are stimulated through interactions within networks…

Abstract

Purpose

The purpose of this paper is to discuss how tacit and explicit knowledge determine grey knowledge and how these are stimulated through interactions within networks, forming the grey hybrid intelligent systems (HISs). The feedback processes and mechanisms between internal and external knowledge determine the apparition of grey knowledge into an intelligent system (IS). The extension of ISs is determined by the ubiquity of the internet but, in our framework, the grey knowledge flows assure the viability and effectiveness of these systems.

Design/methodology/approach

Some characteristics of the Hybrid Intelligent Knowledge Systems are put forward along with a series of models of hybrid computational intelligence architectures. More, relevant examples from the literature related to the hybrid systems architectures are presented, underlying their main advantages and disadvantages.

Findings

Due to the lack of a common framework it remains often difficult to compare the various HISs conceptually and evaluate their performance comparatively. Different applications in different areas are needed for establishing the best combinations between models that are designed using grey, fuzzy, neural network, genetic, evolutionist and other methods. But all these systems are knowledge dependent, the main flow that is used in all parts of every kind of system being the knowledge. Grey knowledge is an important part of the real systems and the study of its proprieties using the methods and techniques of grey system theory remains an important direction of the researches.

Originality/value

The paper discusses the differences among the three types of knowledge and how they and the grey systems theory can be used in different hybrid architectures.

Details

Grey Systems: Theory and Application, vol. 5 no. 2
Type: Research Article
ISSN: 2043-9377

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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…

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

Content available
Article
Publication date: 1 July 2019

Li Xuemei, Yun Cao, Junjie Wang, Yaoguo Dang and Yin Kedong

Research on grey systems is becoming more sophisticated, and grey relational and prediction analyses are receiving close review worldwide. Particularly, the application of…

Abstract

Purpose

Research on grey systems is becoming more sophisticated, and grey relational and prediction analyses are receiving close review worldwide. Particularly, the application of grey systems in marine economics is gaining importance. The purpose of this paper is to summarize and review literature on grey models, providing new directions in their application in the marine economy.

Design/methodology/approach

This paper organized seminal studies on grey systems published by Chinese core journal database – CNKI, Web of Science and Elsevier from 1982 to 2018. After searching the aforementioned database for the said duration, the authors used the CiteSpace visualization tools to analyze them.

Findings

The authors sorted the studies according to their countries/regions, institutions, keywords and categories using the CiteSpace tool; analyzed current research characteristics on grey models; and discussed their possible applications in marine businesses, economy, scientific research and education, marine environment and disasters. Finally, the authors pointed out the development trend of grey models.

Originality/value

Although researches are combining grey theory with fractals, neural networks, fuzzy theory and other methods, the applications, in terms of scope, have still not met the demand. With the increasingly in-depth research in marine economics and management, international marine economic research has entered a new period of development. Grey theory will certainly attract scholars’ attention, and its role in marine economy and management will gain considerable significance.

Details

Marine Economics and Management, vol. 2 no. 2
Type: Research Article
ISSN: 2516-158X

Keywords

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Article
Publication date: 7 August 2017

Naiming Xie

The purpose of this paper is to summarize the different types of grey information, explain the mechanism of grey system modeling and reconstruct the framework of grey

Abstract

Purpose

The purpose of this paper is to summarize the different types of grey information, explain the mechanism of grey system modeling and reconstruct the framework of grey system theory (GST).

Design/methodology/approach

GST has been developed for more than three decades; however, the framework of GST is still in an evolutionary process. This manuscript first explains grey information in detail, and then summarizes a series of grey system models under limited data and poor information. Figures and general steps for different types of grey system models are provided in this paper.

Findings

The findings in this paper clearly differentiate between grey information and other uncertainty information. The differences between grey system models and other uncertainty models are clearly explained. In addition, general steps for different grey system models are given which demonstrate the orientation of grey system modeling.

Practical implications

Theoretical framework is very important for developing a new theory. This paper clarified grey information and grey system-based modeling mechanism. It is very useful to understand and explain the systematic framework of GST and it contributes undoubtedly to make GST perfect.

Originality/value

Grey information is explained in terms of limited data and two types of grey numbers. Accordingly, all of the grey system models were divided into limited data-based grey system models and grey number-based grey system models.

Details

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

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Article
Publication date: 22 March 2013

Zheng‐Xin Wang

The purpose of this paper is to propose a grey linear control system for regulating the price of China's real estate and provide the necessary support to assist the…

Abstract

Purpose

The purpose of this paper is to propose a grey linear control system for regulating the price of China's real estate and provide the necessary support to assist the relevant management departments with their policy making.

Design/methodology/approach

A grey state equation of the real estate market price that can reflect both the market supply‐demand price mechanism and the production price mechanism is proposed based on the economic cybernetics. Also, the grey control linear theory is used to demonstrate the disequilibrium fluctuation control system for the China's real estate market with uncertain parameters.

Findings

The price disequilibrium fluctuation control system for China's real estate market has been in a critical state. The system would reach a balanced state in 2013, if the real estate price in 2010 and 2011 firstly decreased 244.41 yuan/m2 and 62.33 yuan/m2, respectively, and then increased 60.88 yuan/m2 in 2012. The disequilibrium state will continue for years before it reaches a balanced state.

Research limitations/implications

Due to the complexity of operation of grey numbers, the present technique still cannot analyze the properties of the grey control system exactly and further research is needed.

Practical implications

The modelled results can help the relevant management departments steady China's real estate market by price regulation.

Originality/value

A new approach to study the price regulation system of a real estate market is proposed based on grey linear control theory.

Details

Kybernetes, vol. 42 no. 3
Type: Research Article
ISSN: 0368-492X

Keywords

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