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Article
Publication date: 2 November 2015

Dilip Kumar Sen, Saurav Datta and Siba Sankar Mahapatra

Decision making is the task of selecting the most appropriate alternative among a finite set of possible alternatives with respect to some attributes. The attributes may…

Abstract

Purpose

Decision making is the task of selecting the most appropriate alternative among a finite set of possible alternatives with respect to some attributes. The attributes may be subjective or objective (or combination of both), depending upon the situation; requirements may also be conflicting. In practice, most of the real-world decision-making problems are based on subjective evaluation criteria which are basically ill-defined and vague. Since subjective human judgment bears ambiguity and vagueness in the decision making; application of grey numbers set theory may be proved fruitful in this context. The paper aims to discuss these issues.

Design/methodology/approach

Owing to the advantages of grey numbers set theory in tackling subjectivity in decision making; the crisp-TODIM needs to be extended by integrating with grey numbers set theory in order to facilitate decision making consisting of subjective data. Hence, the unified objective of this paper is to propose a grey-based TODIM approach in the context of decision making.

Findings

Application potential of grey-TODIM has been demonstrated through a case empirical robot selection problem. Result obtained thereof, has also been compared to that of existing grey-based decision support systems available in literature.

Originality/value

Application potential of grey-based decision support systems (grey-TOPSIS, grey analysis, grey-MOORA) have been highlighted in available literature resource. However, the shortcoming of these approaches is that they do not consider decision-makers’ risk attitude while decision making. TODIM method is derived from the philosophy of Cumulative Prospect Theory (CPT) which considers risk averting attitude of the decision maker in case of gain and risk seeking attitude in case of loss, while comparing dominance between two alternatives with respect to a particular criterion. Hence, this paper contributes a mathematical foundation of TODIM coupled with grey numbers set theory for logical decision making.

Details

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

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Article
Publication date: 28 January 2014

Jun Liu and Jian-Zhong Qiao

Due to the limitation of acknowledgment, the complexity of software system and the interference of noises, this paper aims to solve the traditional problem: traditional…

Abstract

Purpose

Due to the limitation of acknowledgment, the complexity of software system and the interference of noises, this paper aims to solve the traditional problem: traditional software cost estimation methods face the challenge of poor and uncertain inputs.

Design/methodology/approach

Under such circumstances, different cost estimation methods vary greatly on estimation accuracy and effectiveness. Therefore, it is crucial to perform evaluation and selection on estimation methods against a poor information database. This paper presents a grey rough set model by introducing grey system theory into rough set based analysis, aiming for a better choice of software cost estimation method on accuracy and effectiveness.

Findings

The results are very encouraging in the sense of comparison among four machine learning techniques and thus indicate it an effective approach to evaluate software cost estimation method where insufficient information is provided.

Practical implications

Based on the grey rough set model, the decision targets can be classified approximately. Furthermore, the grey of information and the limitation of cognition can be overcome during the use of the grey rough interval correlation cluster method.

Originality/value

This paper proposed the grey rough set model combining grey system theory with rough set for software cost estimation method evaluation and selection.

Details

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

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Article
Publication date: 10 April 2009

Qiao‐Xing Li and Si‐Feng Liu

The purpose of this paper is to explain the connotation of grey number, which is the basic unit of grey mathematics and the key to establish the mathematic framework of…

Abstract

Purpose

The purpose of this paper is to explain the connotation of grey number, which is the basic unit of grey mathematics and the key to establish the mathematic framework of grey system theory.

Design/methodology/approach

From the grey hazy set, the paper re‐defines grey number and the operation of grey‐number element, then some properties are obtained. Based on them, the operation of grey‐matrix element is given. The general definition of grey function and its operation are also proposed.

Findings

The connotation of grey number is elaborated and the elementary framework of grey mathematics can be established.

Research limitations/implications

The researched object, objective and techniques of grey system theory have not been logically proposed and they may influence the comprehension of grey system theory. The obtained results of grey mathematics may significantly promote its development.

Practical implications

The paper can enable managers to control the complex system with missing information by using the quantitative approaches.

Originality/value

Grey mathematics may become a branch of mathematics to deal with proximate calculation.

Details

Kybernetes, vol. 38 no. 3/4
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 18 August 2020

Shi Quan Jiang, SiFeng Liu and ZhongXia Liu

The purpose of this paper is to study the grey decision model and distance measuring method of general grey number.

Abstract

Purpose

The purpose of this paper is to study the grey decision model and distance measuring method of general grey number.

Design/methodology/approach

First, intuitionistic grey number (IGN) set and an IGN are defined by grey number probability function. Second, each interval grey number in general grey number is represented by an IGN and converts the general grey number into an IGN set. Final, the operation of two general grey numbers is defined as the operation between IGN sets, and the distance measure of the general grey number is given.

Findings

Up to now, the method of measuring the distance and the grey decision model of general grey number is established. Thus, the difficult problem for set up decision mode of general grey number has been solved to a certain degree.

Research limitations/implications

The method exposed in this paper can be used to integrate information form a different source. The method that a general grey number converted to a set of IGNs could be extended to the case of grey incidence analysis models, grey prediction models and grey clustering evaluation models, which includes general grey numbers, etc.

Originality/value

The concepts of IGN and IGN set are proposed for the first time in this paper; The operation of two general grey numbers can be defined as the operation between IGN sets. On this basis, the algorithm of IGN, the integration operator of IGN and the distance measure between IGN sets are given.

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: 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

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Article
Publication date: 1 April 2021

Tooraj Karimi and Arvin Hojati

The purpose of this paper is to design an inference engine to measure the level of readiness of each bank before starting the corporate sustainability auditing process…

Abstract

Purpose

The purpose of this paper is to design an inference engine to measure the level of readiness of each bank before starting the corporate sustainability auditing process. Based on the output of the designed inference engine, the audition team can decide about the audition resources and the auditing process.

Design/methodology/approach

In this paper, the hybrid rough and grey set theory are used to design and create a rule model system to measure the sustainability level of banks. First, 16 rule models are extracted using rough set theory (RST), and the cross-validation of each model is done. Then, the grey clustering is used to combine the same condition attributes and improve the validity of the final model. A total of 16 new rule models are extracted based on the decreased condition attributes, and the best model is selected based on the cross-validation results.

Findings

By comparing the accuracy of rough-gray’s rule models and as a result of decreasing the condition attributes, a proper increase in the accuracy of all models is obtained. Finally, the Naive/Genetic/object-related reducts model with 95.6% accuracy is selected as an inference engine to measure new banks’ readiness level.

Originality/value

Sustainability measurement of banks based on RST is a new approach in the field of corporate sustainability. Furthermore, using the grey clustering for combining the condition attributes is a novel solution for improving the accuracy of the rule models.

Details

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

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Article
Publication date: 5 April 2019

Mohamad Amin Kaviani, Amir Karbassi Yazdi, Lanndon Ocampo and Simonov Kusi-Sarpong

The oil and gas industry is a crucial economic sector for both developed and developing economies. Delays in extraction and refining of these resources would adversely…

Abstract

Purpose

The oil and gas industry is a crucial economic sector for both developed and developing economies. Delays in extraction and refining of these resources would adversely affect industrial players, including that of the host countries. Supplier selection is one of the most important decisions taken by managers of this industry that affect their supply chain operations. However, determining suitable suppliers to work with has become a phenomenon faced by these managers and their organizations. Furthermore, identifying relevant, critical and important criteria needed to guide these managers and their organizations for supplier selection decisions has become even more complicated due to various criteria that need to be taken into consideration. With limited works in the current literature of supplier selection in the oil and gas industry having major methodological drawbacks, the purpose of this paper is to develop an integrated approach for supplier selection in the oil and gas industry.

Design/methodology/approach

To address this problem, this paper proposes a new uncertain decision framework. A grey-Delphi approach is first applied to aid in the evaluation and refinement of these various available criteria to obtain the most important and relevant criteria for the oil and gas industry. The grey systems theoretic concept is adopted to address the subjectivity and uncertainty in human judgments. The grey-Shannon entropy approach is used to determine the criteria weights, and finally, the grey-EDAS (evaluation based on distance from average solution) method is utilized for determining the ranking of the suppliers.

Findings

To exemplify the applicability and robustness of the proposed approach, this study uses the oil and gas industry of Iran as a case in point. From the literature review, 21 criteria were established and using the grey-Delphi approach, 16 were finally considered. The four top-ranked criteria, using grey-Shannon entropy, include warranty level and experience time, relationship closeness, supplier’s technical level and risks which are considered as the most critical and influential criteria for supplier evaluation in the Iranian oil and gas industry. The ranking of the suppliers is obtained, and the best and worst suppliers are also identified. Sensitivity analysis indicates that the results using the proposed methodology are robust.

Research limitations/implications

The proposed approach would assist supply chain practicing managers, including purchasing managers, procurement managers and supply chain managers in the oil and gas and other industries, to effectively select suitable suppliers for cooperation. It can also be used for other multi-criteria decision-making (MCDM) applications. Future works on applying other MCDM methods and comparing them with the results of this study can be addressed. Finally, broader and more empirical works are required in the oil and gas industry.

Originality/value

This study is among the first few studies of supplier selection in the oil and gas industry from an emerging economy perspective and sets the stage for future research. The proposed integrated grey-based MCDM approach provides robust results in supplier evaluation and can be used for future domain applications.

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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

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Article
Publication date: 13 February 2017

Anoop Kumar Sahu, Atul Kumar Sahu and Nitin Kumar Sahu

In present research, the authors conducted the massive literature review and collected the information, in regards to material handling system (MHS) to build a multi…

Abstract

Purpose

In present research, the authors conducted the massive literature review and collected the information, in regards to material handling system (MHS) to build a multi criteria MHS hierarchical module consists of ecological cum fiscal criteria. Moreover, similar literature review assisted the authors to resolve and eventually construct the effectual and robust approach. The purpose of this paper is to facilitate the managers for benchmarking the MHS alternatives operating under similar module via robust decision support system (DSS).

Design/methodology/approach

In present research, the proposed module dealt with ecological (subjective) and fiscal (objective) criteria, where subjective criteria associated with incompleteness, vagueness, imprecision, as well as inconsistency, solicited the discrete information in terms of Grey set via linguistic scale from experts panel. The objective information (capital) has been assigned by expert’s panel in terms of Grey set. To robustly evaluate and select the admirable MHS, three approaches named: degree of possibility, technique for order preference similar to ideal solution as well as Grey relational analysis fruitfully applied to connect and unite discrete information.

Findings

The performance evaluation of MHSs has been carried out under concert of individual fiscal criteria excluding ecological criteria in past researches. Moreover the previous developed DSS tackled sole approach under individual fiscal criteria. The authors found the broad applications of fuzzy sets except Grey set theory in the same context for measuring the performance of MHS alternatives. Aforesaid research gaps have been transformed into research objectives by incorporating the module for both fiscal cum ecological criteria. This research embraces a robust DSS, which has been explored to select the admirable MHS alternative.

Originality/value

An empirical case study has been carried out in order to demonstrate the legitimacy of holistic Grey-MCDM method, implemented over multi criteria MHS hierarchical module. Proposed DSS seems to be the best for organisations, which believe to appraise and select the MHS including fiscal as well as ecological criteria excluding individual fiscal criteria. Moreover, subjective cum objective or individual subjective or objective criteria can be extended with respect to varieties of MHSs.

Details

The International Journal of Logistics Management, vol. 28 no. 1
Type: Research Article
ISSN: 0957-4093

Keywords

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Article
Publication date: 18 June 2020

Tooraj Karimi and Arvin Hojati

In this study, a hybrid rough and grey set-based rule model is designed for diagnosis of one type of blood cancer called multiple myeloma (MM). The grey clustering method…

Abstract

Purpose

In this study, a hybrid rough and grey set-based rule model is designed for diagnosis of one type of blood cancer called multiple myeloma (MM). The grey clustering method is used to combine the same condition attributes and to improve the validity of the final model.

Design/methodology/approach

Some tools of the rough set theory (RST) and grey incidence analysis (GIA) are used in this research to analyze the serum protein electrophoresis (SPE) test results. An RST-based rule model is extracted based on the laboratory SPE test results of patients. Also, one decision attribute and 15 condition attributes are used to extract the rules. About four rule models are constructed due to the different algorithms of data complement, discretization, reduction and rule generation. In the following phases, the condition attributes are clustered into seven clusters by using a grey clustering method, the value set of the decision attribute is decreased by using manual discretizing and the number of observations is increased in order to improve the accuracy of the model. Cross-validation is used for evaluation of the model results and finally, the best model is chosen with 5,216 rules and 98% accuracy.

Findings

In this paper, a new rule model with high accuracy is extracted based on the combination of the grey clustering method and RST modeling for diagnosis of the MM disease. Also, four primary rule models and four improved rule models have been extracted from different decision tables in order to define the result of SPE test of patients. The maximum average accuracy of improved models is equal to 95% and related to the gamma globulins percentage attribute/object-related reducts (GA/ORR) model.

Research limitations/implications

The total number of observations for rule extraction is 115 and the results can be improved by further samples. To make the designed expert system handy in the laboratory, new computer software is under construction to import data automatically from the electrophoresis machine into the resultant rule model system.

Originality/value

The main originality of this paper is to use the RST and GST together to design and create a hybrid rule model to diagnose MM. Although many studies have been carried out on designing expert systems in medicine and cancer diagnosis, no studies have been found in designing systems to diagnose MM. On the other hand, using the grey clustering method for combining the condition attributes is a novel solution for improving the accuracy of the rule model.

Details

Grey Systems: Theory and Application, vol. 10 no. 4
Type: Research Article
ISSN: 2043-9377

Keywords

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