scholarly journals Performance Assessment of Engineering Educational Institutes in Madhya Pradesh using Topsis and GRA

2019 ◽  
Vol 9 (2) ◽  
pp. 2844-2855
Keyword(s):  
Performance Assessment ◽  
Central India ◽  
The State ◽  
Madhya Pradesh ◽  
Educational Institutions ◽  
Relational Analysis ◽  
Order Preference ◽  
Technical Manpower ◽  
Grey Relational ◽  
The Ideal

This paper uses multi criteria decision making methods to measure the performance assessment in engineering educational institutions in the state of Madhya Pradesh, India. To cater the need of technical manpower, a very large number of private engineering colleges have been established in the state of Madhya Pradesh of central India within a short span. The diminishing quality made so many engineering colleges forced towards closure is a concern in the state today. Therefore, the need for performance assessment and ranking of these engineering institutions is predominant. For the proposed framework, Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) and Grey Relational Analysis methods are applied for performance assessment of 28 engineering educational institutions taking into account some selected criteria.

scholarly journals A comparison of TOPSIS, grey relational analysis and COPRAS methods for machine selection problem in the food industry of Turkey

2021 ◽  
Vol 9 (2) ◽  
pp. 81
Author(s):  
Sami Özcan ◽  
Ali Kemal Çelik
Keyword(s):  
Decision Making ◽  
Grey Relational Analysis ◽  
Entropy Method ◽  
Sensitivity Analyses ◽  
Food Sector ◽  
Relational Analysis ◽  
Machine Selection ◽  
Order Preference ◽  
Topsis Technique ◽  
Grey Relational

<div data-canvas-width="540.0693333333334">The paper aims to compare the results of the selection/choice of cream separators by using multi-criteria decision-making methods in an integrated manner for an enterprise with a dairy processing capacity of 80 to 100 tons per day operating in the Turkish food sector. A total of 7 alternative products and 7 criteria for milk processing were determined. Criterion weights were calculated using entropy method and then integrated into TOPSIS (Technique for Order Preference by Similarity to Ideal Solutions), GRA (Grey Relational Analysis) and COPRAS (Complex Proportional Assessment) methods. Sensitivity analyses were carried out on the results obtained from the three methods to check for their reliability. At the end of the study, similar alternative and appropriate results were found from the TOPSIS and COPRAS methods. However, different alternative but appropriate or suitable results were obtained from the GRA method. Sensitivity analysis of the three methods showed that all the methods used were valid. In the review of available and related literature, very few studies on machine selection in the dairy and food sector in general were found. For this reason, it is thought that the study will contribute to the decision-making process of companies in the dairy sector in their choice of machinery selections. As far as is known, this paper is the first attempt in extant literature to compare in an integrated manner the results of TOPSIS, COPRAS and GRA methods considered in the study.</div>

scholarly journals DEA Cross-Efficiency Ranking Method Based on Grey Correlation Degree and Relative Entropy

Entropy ◽  
2019 ◽  
Vol 21 (10) ◽  
pp. 966 ◽  
Author(s):  
Si ◽  
Ma
Keyword(s):  
Relative Entropy ◽  
Evaluation Method ◽  
Ideal Solution ◽  
Analysis Method ◽  
Relational Analysis ◽  
Correlation Degree ◽  
Efficiency Ranking ◽  
Grey Correlation Degree ◽  
Grey Relational ◽  
The Ideal

The ranking of decision-making units (DMUs) is one of the most significant issues in efficiency evaluation. However, the calculation results from the traditional DEA method sometimes include multiple efficient DMUs or multiple DMUs with the same efficiency value, in which case the approach is weak in distinguishing among these DMUs. Therefore, this study proposes a DEA cross-efficiency ranking method based on the relative entropy evaluation method and the grey relational analysis method. First, the approach uses the cross-efficiency matrix as the decision matrix of multiple criteria decision-making (MCDM), and the relationship between DMU and the ideal solution is analyzed by the grey relational analysis method and the relative entropy evaluation method. Then, the degree of the criteria is determined by Shannon entropy, and the weighted grey correlation degree and the weighted relative entropy are obtained. Finally, with the comprehensive relative closeness degree between the DMU and the ideal solution, we can sort all the DMUs accordingly. In a comparative analysis, it shows that this method analyzes the similarity between DMUs and the ideal solution from the information distance and the similarity of the data sequence curve, and has certain advantages for analyzing the ranking of DMUs.

scholarly journals Reptilian diversity of the Bhopal Region in the State of Madhya Pradesh in central India

2018 ◽  
Vol 25 (2) ◽  
pp. 104-114
Author(s):  
Amit Manhas ◽  
Rajni Raina ◽  
Ashwani Wanganeo
Keyword(s):  
Central India ◽  
The State ◽  
Baseline Data ◽  
Madhya Pradesh ◽  
Monsoon Period ◽  
Wide Range

The wide range of habitats in the Bhopal Region of Madhya Pradesh in central India support a rich reptilian fauna. Conducting visual surveys, we recorded 34 species of reptiles (2 species of crocodilians, 3 species of turtles, 13 species of lizards, 16 species of snakes). Observations were made during the monsoon period from mid-June to mid-September in 2014-2015. Herein, we present baseline data regarding the reptilian fauna of the Bhopal Region.

scholarly journals Three-Way Decisions with Single-Valued Neutrosophic Decision Theory Rough Sets Based on Grey Relational Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Peide Liu ◽  
Hongyu Yang
Keyword(s):  
Decision Making ◽  
Decision Theory ◽  
Conditional Probability ◽  
Grey Relational Analysis ◽  
Neutrosophic Set ◽  
Ideal Solution ◽  
Relational Analysis ◽  
Model Based ◽  
Grey Relational ◽  
The Ideal

The single-valued neutrosophic set (SVNS) can not only depict imperfect information in the real decision system but also handle undetermined and inconformity information flexibly and effectively. Three-way decisions (3WDs) are often used as an effective method to deal with uncertainties, but the conditional probability is given by the decision maker subjectively, which makes the decision result too subjective. This paper proposes a novel model based on 3WDs to settle the multiattribute decision-making (MADM) problems, where the attribute values are described by SVNS, and the attribute weights are entirely unknown. At first, we build a single-valued neutrosophic decision theory rough set (SVNDTRS) model based on Bayesian decision process. Then, we use the analytic hierarchy process (AHP) approach to calculate the subjective weight of each attribute, the information entropy to obtain the attribute’s objective weight, and the minimum total deviation approach to determine the combined weight of the attributes. After obtaining the standard weight, the grey relational analysis (GRA) method is utilized to calculate the grey correlation closeness with the ideal solution, and the conditional probability is estimated by it. In addition, we develop a decision-making method in view of the ideal solution of 3WDs with the SVNS. This approach not only considers the lowest cost but also gives a corresponding semantic explanation for the decision result of each alternative, which can supplement the decision results of GRA. At last, we illustrate the feasibility and effectiveness of 3WDs through an example of supplier selection and compare it with other methods to verify the advantages of our approach.

scholarly journals Financial Performance Assessment of Non-Life Insurance Companies Traded in Borsa Istanbul via Grey Relational Analysis

2016 ◽  
Vol 8 (4) ◽  
pp. 277 ◽  
Author(s):  
Emine Oner Kaya
Keyword(s):  
Financial Performance ◽  
Performance Assessment ◽  
Life Insurance ◽  
Grey Relational Analysis ◽  
Capital Adequacy ◽  
Financial Ratios ◽  
Insurance Companies ◽  
Relational Analysis ◽  
Grey Relational ◽  
Profitability Ratios

<p>The analysis of the financial performances of non-life insurance companies traded in Borsa Istanbul (BIST) as of the end of 2014 via the grey relational analysis (GRA) method has been aimed in this study. Financial performances of non-life insurance companies in the 2010 to 2014 period have been examined in terms of the capital adequacy ratios, liquidity ratios, operating ratios, and profitability ratios. The results of the GRA based on 16 financial ratios indicate that Aksigorta has been ranked first and Unico Sigorta has been ranked last in terms of financial performance for the 2010 to 2014 period. The results also show that profitability ratios have the greatest impact on the financial performance of non-life insurance companies traded in BIST.</p>

Multi-terms MADM procedures with GRA and TOPSIS based on IFS and IVIFS

2014 ◽  
Vol 4 (2) ◽  
pp. 164-185 ◽  
Author(s):  
Ozkan Bali ◽  
Serkan Gumus
Keyword(s):  
Intuitionistic Fuzzy Set ◽  
Aggregation Operators ◽  
Past Performance ◽  
Content Type ◽  
Relational Analysis ◽  
Intuitionistic Fuzzy ◽  
Order Preference ◽  
The Right ◽  
Grey Relational ◽  
Interval Valued

Purpose – In the literature, many multi attributes decision making (MADM) models allow evaluation of the alternatives considering their current or last performance. However, in some MADM problems, not only current performance of alternatives but also their past performance should be taken into account in order to select the most appropriate alternative. For this reason, the purpose of this paper is to develop four procedures to evaluate the alternatives in MADM problems with multi terms. Design/methodology/approach – This study uses dynamic operators to aggregate the evaluation in different terms and then, grey relational analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS) methods are utilized to determine the most appropriate alternative. Thus, four procedures which consist of these operators and methods are developed to evaluate the alternatives in multi terms. Findings – Some numerical examples are presented for the proposed procedures in multi-terms. Moreover, these four procedures are compared with other four procedures. The analyses of the results show that dynamic aggregation operators based on intuitionistic fuzzy set (IFS) and interval valued intuitionistic fuzzy sets (IVIFS) with GRA and TOPSIS can be used jointly for MADM problems in which alternatives are evaluated for different terms. Originality/value – One of the significant mistakes faced in some MADM problems is to take into account the current performance of alternatives or is to ignore their past performance. The right selection depends on past and current performance of the alternatives. The novelty of this study is to propose four procedures for solving MADM problems in multi terms based on IFS and IVIFS using dynamic aggregation operators and GRA and TOPSIS methods.

Developing MCDM Approach Based on GRA and TOPSIS

2010 ◽  
Vol 34-35 ◽  
pp. 1931-1935 ◽  
Author(s):  
Qi Bing Wang ◽  
An Hua Peng
Keyword(s):  
Decision Making ◽  
Comprehensive Evaluation ◽  
Multiple Criteria Decision Making ◽  
Fuzzy Comprehensive Evaluation ◽  
Multiple Criteria ◽  
Shape Similarity ◽  
Ideal Solution ◽  
Relational Analysis ◽  
Order Preference ◽  
Grey Relational

Multiple criteria decision making(MCDM) is widely used in selection from a set of available alternatives with multiple criteria, approaches to which includes fuzzy comprehensive evaluation(FCE), grey relational analysis(GRA), and technique for order preference by similarity to ideal solution(TOPSIS), and so on. First analyzes the limitations of various methods: only considering the overall effect of attribute indicators in the method of FCE, only considering the shape similarity of data curve between comparative scheme and ideal solution in GRA and only considering position approximation in TOPSIS. Second proposes a new method of comprehensive evaluation which takes into account both shape similarity and position approximation. The validity of this method has been further proved by an example of suppliers selection.

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