scholarly journals A Grey Interval Relational Degree-Based Dynamic Multiattribute Decision Making Method and Its Application in Investment Decision Making

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Yuhong Wang ◽  
Xiaojuan Shi ◽  
Jihong Sun ◽  
Wuyong Qian
Keyword(s):  
Decision Making ◽  
Investment Decision ◽  
Three Dimensional ◽  
Observation Data ◽  
Interval Numbers ◽  
Investment Decision Making ◽  
Decision Making Problem ◽  
Grey Relational Degree ◽  
Relational Degree ◽  
Grey Relational

The purpose of this paper is to propose a three-dimensional grey interval relational degree model for dynamic Multiattribute decision making. In the model, the observed values are interval grey numbers. Elements are selected in the system as the points in anm-dimensional linear space. Then observation data of each element to different time and objects are as the coordinates of point. An optimization model is employed to obtain each scheme’s affiliate degree for the positive and negative ideal schemes. And a three-dimensional grey interval relational degree model based on time, index, and scheme is constructed in the paper. The result shows that the three-dimensional grey relational degree simplifies the traditional dynamic multiattribute decision making method and can better resolve the dynamic multiattribute decision making problem of interval numbers. The example illustrates that the method presented in the paper can be used to deal with problems of uncertainty such as dynamic multiattribute decision making.

Study on Divergence Based on the Grey Relational Degree in the Group Decision-Making

2010 ◽  
Vol 29-32 ◽  
pp. 1168-1174
Author(s):  
Jun Ying Wang ◽  
De Hua Li ◽  
Shi Hong Wu
Keyword(s):  
Decision Making ◽  
Theoretical Basis ◽  
Group Decision ◽  
Expert Group ◽  
Research Model ◽  
Grey Relational Degree ◽  
Relational Degree ◽  
Machine Interface ◽  
Grey Relational ◽  
Individual Expert

Expert is a very important factor that affects the outcome of decision-making. This paper applies the grey relational degree in measuring the similarity on the evaluation of decision-making scheme between individual expert and expert group, and establishes the research model of expert's decision-making divergence, which provides some theoretical basis for expert’s evaluative reliability and fairness, reveals some possible bias in attribute understanding as well as important deficiencies or loopholes that existed in schemes. Besides, it provides a better way of man-machine interface for hall for workingshop of metasynthetic (HWME) and a good chance for further discussion about minority’s different opinions. Finally, the approach is proved to be effective in revealing the divergence and deviation of decision making through the example.

scholarly journals Energy-Investment Decision-Making for Industry: Quantitative and Qualitative Risks Integrated Analysis

2021 ◽  
Vol 13 (12) ◽  
pp. 6977
Author(s):  
Eva M. Urbano ◽  
Victor Martinez-Viol ◽  
Konstantinos Kampouropoulos ◽  
Luis Romeral
Keyword(s):  
Decision Making ◽  
Cost Benefit Analysis ◽  
Investment Decision ◽  
Energy Transition ◽  
Integrated Analysis ◽  
Energy Investment ◽  
Inference System ◽  
Investment Decision Making ◽  
Decision Making Problem ◽  
Energy Equipment

Industrial SMEs may take the decision to invest in energy efficient equipment to reduce energy costs by replacing or upgrading their obsolete equipment or due to external socio-political and legislative pressures. When upgrading their energy equipment, it may be beneficial to consider the adoption of new energy strategies rising from the ongoing energy transition to support green transformation and decarbonisation. To face this energy-investment decision-making problem, a set of different economic and environmental criteria have to be evaluated together with their associated risks. Although energy-investment problems have been treated in the literature, the incorporation of both quantitative and qualitative risks for decision-making in SMEs has not been studied yet. In this paper, this research gap is addressed, creating a framework that considers non-risk criteria and quantitative and qualitative risks into energy-investment decision-making problems. Both types of risks are evaluated according to their probability and impact on the company’s objectives and, additionally for qualitative risks, a fuzzy inference system is employed to account for judgmental subjectivity. All the criteria are incorporated into a single cost–benefit analysis function, which is optimised along the energy assets’ lifetime to reach the best long-term energy investment decisions. The proposed methodology is applied to a specific industrial SME as a case study, showing the benefits of considering these risks in the decision-making problem. Nonetheless, the methodology is expandable with minor changes to other entities facing the challenge to invest in energy equipment or, as well, other tangible assets.

scholarly journals Grey Relational Analysis for Hesitant Fuzzy Sets and Its Applications to Multiattribute Decision-Making

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Xin Guan ◽  
Guidong Sun ◽  
Xiao Yi ◽  
Jing Zhao
Keyword(s):  
Decision Making ◽  
Grey Relational Analysis ◽  
Correlation Coefficients ◽  
Hesitant Fuzzy Set ◽  
Fuzzy Measures ◽  
Information Measures ◽  
Relational Analysis ◽  
Grey Relational Degree ◽  
Relational Degree ◽  
Grey Relational

Due to the superiority in expressing the uncertain and vague information, the hesitant fuzzy set (HFS) is regarded as an important tool to deal with multiattribute decision-making (MADM) problems. Quantitative and qualitative fuzzy measures have been proposed to solve such problems from different points. However, most of the existing information measures for HFSs are related to such fuzzy measures as distance, similarity, entropy, and correlation coefficients. The grey relational analysis is omitted. Besides, the existing grey relational analysis for HFSs only considers the range or distance between HFSs data which is only a partial measure of the HFSs. Therefore, in this paper, we improve the grey relational analysis for HFSs and explore a novel slope grey relational degree by considering another factor of HFSs data: the slope. Further, we combine both the distance and slope factors of HFSs data to construct a synthetic grey relational degree that describes the closeness and variation tendency of HFSs simultaneously, greatly enriching the fuzzy measures of HFSs. Furthermore, with the help of the TOPSIS method, we develop the grey relational based MADM methodology to solve the HFSs MADM problems. Finally, combining with two practical MADM examples about energy policy selection and multisensor target recognition, we obtain the most desirable decision results. Compared with the previous methods, the validity, comprehensiveness, and discrimination of the proposed synthetic grey relational degree for HFSs are demonstrated in detail.

scholarly journals Multi-criteria decision making based on induced generalized interval neutrosophic Choquet integral

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0242449
Author(s):  
Yangyang Jiao ◽  
Lu Wang ◽  
Jianxia Liu ◽  
Gang Ma
Keyword(s):  
Decision Making ◽  
Choquet Integral ◽  
Investment Decision ◽  
Aggregation Operators ◽  
Optimal Decision ◽  
Multi Criteria Decision Making ◽  
Investment Decision Making ◽  
Decision Making Problem ◽  
Geometric Operator ◽  
Integral Average

In this paper, two new aggregation operators based on Choquet integral, namely the induced generalized interval neutrosophic Choquet integral average operator(IGINCIA) and the induced generalized interval neutrosophic Choquet integral geometric operator(IG-INCIG), are proposed for multi-criteria decision making problems (MCDM). Firstly, the criteria are dependent to each other and the evaluation information of the criteria are expressed by interval neutrosophic numbers. Moreover, two indices which are inspired by the geometrical structure are established to compare the interval neutrosophic numbers. Then, a MCDM method is proposed based on the proposed aggregation operators and ranking indices to cope with MCDM with interactive criteria. Lastly, an investment decision making problem is provided to illustrate the practicality and effectiveness of the proposed approach. The validity and advantages of the proposed method are analyzed by comparing with some existing approaches. By a numerical example in company investment to expand business though five alternatives with considering four criteria, the optimal decision is made.

Composite Fuzzy Measure and its Application to Decision-Making

2004 ◽  
Vol 8 (3) ◽  
pp. 252-259
Author(s):  
Toshihiro Kaino ◽  
◽  
Kaoru Hirota ◽  
Keyword(s):  
Decision Making ◽  
Capital Investment ◽  
Choquet Integral ◽  
Investment Decision ◽  
Measurable Space ◽  
Fuzzy Measure ◽  
Fuzzy Measures ◽  
Investment Decision Making ◽  
Decision Making Problem ◽  
Fuzzy Weights

In applications using fuzzy measures (on real numbers), it becomes a problem how to evaluate in-between intervals each characterized by a fuzzy measure, especially when the Choquet integral is differentiated in real world problems. A composite fuzzy measure built from fuzzy measures defined on fuzzy measurable spaces has been proposed by Kaino and Hirota using composite fuzzy weights, where the measurable space of this composite fuzzy measure is the direct sum of measurable spaces. An associative, composite fuzzy measure built from a finite number of fuzzy measures is proposed and, in a constructive application, it is applied to the automobile plant capital investment decision-making problem. It is assumed that an automobile company plans to sell a new car. The current plant line has a capacity of 3,200 new cars in addition to current car lines. Using this composite fuzzy measure, differentiation of the Choquet integral becomes a quantitative index for decision-making, which is confirmed by this decision-making experiment.

scholarly journals Group decision-making using improved multi-criteria decision making methods for credit risk analysis

Filomat ◽  
2016 ◽  
Vol 30 (15) ◽  
pp. 4135-4150 ◽  
Author(s):  
Wenshuai Wu ◽  
Gang Kou ◽  
Yi Peng
Keyword(s):  
Decision Making ◽  
Risk Analysis ◽  
Credit Risk ◽  
Group Decision Making ◽  
Group Decision ◽  
Ideal Solution ◽  
Grey Relational Degree ◽  
Relational Degree ◽  
Credit Risk Analysis ◽  
Grey Relational

Credit risk analysis is a core research issue in the field of financial risk management. This paper first investigates the analytic hierarchy process (AHP) as a method of measuring index weights for group decision-making (GDM). AHP for group decision-making (AHP-GDM) is then researched and applied, taking into full account the cognitive levels of different experts. Second, the concept of grey relational degree is introduced into the ideal solution of the technique for order of preference by similarity to ideal solution (TOPSIS). This concept fully considers the relative closeness of grey relational degree between alternatives and the ?ideal? solution in order to strengthen their relationship. The AHP-GDM method overcomes the problem of subjectivity in measuring index weights, and the revised TOPSIS (R-TOPSIS) method heightens the effectiveness of assessment results. An illustrative case using data from Chinese listed commercial banks shows that the R-TOPSIS method is more effective than both TOPSIS and grey relational analysis (GRA) in credit risk evaluation. The two improved multi-criteria decision making (MCDM) methods are also applied to empirical research regarding the credit risk analysis of Chinese urban commercial banks. The results indicate the validity and effectiveness of both methods.

The role of affective reactions on investment decision-making

2007 ◽  
Author(s):  
Enrico Rubaltelli ◽  
Giacomo Pasini ◽  
Rino Rumiati ◽  
Paul Slovic
Keyword(s):  
Decision Making ◽  
Investment Decision ◽  
Affective Reactions ◽  
Investment Decision Making
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