scholarly journals A Novel Extension of the Technique for Order Preference by Similarity to Ideal Solution Method with Objective Criteria Weights for Group Decision Making with Interval Numbers

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1460
Author(s):  
Dariusz Kacprzak
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Ease Of Use ◽  
Decision Makers ◽  
Ideal Solution ◽  
Interval Numbers ◽  
Group Matrix ◽  
Order Preference ◽  
Criteria Weights

This paper presents an extension of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method with objective criteria weights for Group Decision Making (GDM) with Interval Numbers (INs). The proposed method is an alternative to popular and often used methods that aggregate the decision matrices provided by the decision makers (DMs) into a single group matrix, which is the basis for determining objective criteria weights and ranking the alternatives. It does not use an aggregation operator, but a transformation of the decision matrices into criteria matrices, in the case of determining objective criteria weights, and into alternative matrices, in the case of the ranking of alternatives. This ensures that all the decision makers’ evaluations are taken into account instead of their certain average. The numerical example shows the ease of use of the proposed method, which can be implemented into common data analysis software such as Excel.

scholarly journals Hybrid Multiattribute Group Decision Making Based on Intuitionistic Fuzzy Information and GRA Method

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Jian Guo
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Ideal Solution ◽  
Decision Matrix ◽  
Intuitionistic Fuzzy ◽  
Multiple Attribute ◽  
Intuitionistic Fuzzy Entropy ◽  
Fuzzy Group Decision Making

Hybrid multiple attribute group decision making involves ranking and selecting competing courses of action available using attributes to evaluate the alternatives. The decision makers assessment information can be expressed in the form of real number, interval-valued number, linguistic variable, and the intuitionistic fuzzy number. All these evaluation information can be transformed to the form of intuitionistic fuzzy numbers. A combined GRA with intuitionistic fuzzy group decision-making approach is proposed. Firstly, the hybrid decision matrix is standardized and then transformed into an intuitionistic fuzzy decision matrix. Then, intuitionistic fuzzy averaging operator is utilized to aggregate opinions of decision makers. Intuitionistic fuzzy entropy is utilized to obtain the entropy weights of the criteria, respectively. After intuitionistic fuzzy positive ideal solution and intuitionistic fuzzy negative ideal solution are calculated, the grey relative relational degree of alternatives is obtained and alternatives are ranked. In the end, a numerical example illustrates the validity and applicability of the proposed method.

scholarly journals A BI-OBJECTIVE SCORE-VARIANCE BASED LINEAR ASSIGNMENT METHOD FOR GROUP DECISION MAKING WITH HESITANT FUZZY LINGUISTIC TERM SETS

2018 ◽  
Vol 24 (3) ◽  
pp. 1125-1148 ◽  
Author(s):  
Seyed Hossein RAZAVI HAJIAGHA ◽  
Meisam SHAHBAZI ◽  
Hannan AMOOZAD MAHDIRAJI ◽  
Hossein PANAHIAN
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Assignment Method ◽  
Linguistic Term ◽  
Criteria Weights ◽  
Individual Evaluation ◽  
Fuzzy Linguistic ◽  
Linear Assignment

Decision makers usually prefer to express their preferences by linguistic variables. Classic fuzzy sets allowed expressing these preferences using a single linguistic value. Considering inevitable hesitancy of decision makers, hesitant fuzzy linguistic term sets allowed them to express individual evaluation using several linguistic values. Therefore, these sets improve the ability of humans to determine believes using their own language. Considering this feature, in this paper a method upon linear assignment method is proposed to solve group decision making problems using this kind of information, when criteria weights are known or unknown. The performance of the proposed method is illustrated in a numerical example and the results are compared with other methods to delineate the models efficiency. Following a logical and well-known mathematical logic along with simplicity of execution are the main advantages of the proposed method.

scholarly journals AN INTEGRATED FUZZY MULTI CRITERIA GROUP DECISION MAKING MODEL FOR HANDLING EQUIPMENT SELECTION

2014 ◽  
Vol 20 (5) ◽  
pp. 660-673 ◽  
Author(s):  
Abdolreza Yazdani-Chamzini
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Ahp ◽  
Evaluation Model ◽  
Evaluation Criteria ◽  
Fuzzy Topsis ◽  
Equipment Selection ◽  
Order Preference ◽  
Criteria Weights

The problem of handling equipment selection plays a significant role in the total cost of a mining project; so that it can affect the activity and continuity of the project and is a strategic problem. In this study, an integrated model based on two fuzzy multi-criteria decision making techniques for handling equipment selection is proposed. The proposed evaluation model is derived from group decision making, fuzzy set theory, analytical hierarchy process (AHP), and Technique to Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The fuzzy AHP (FAHP) method is utilized to calculate the relative importance of the evaluation criteria, then, fuzzy TOPSIS (FTOPSIS) is applied for evaluating the feasible handling equipment in order to select the best handling system among a pool of the possible alternatives. The model is applied for a real world case study to demonstrate the capability and effectiveness of the proposed model. To investigate the result sensitiveness to the changes of the criteria weights, a sensitivity analysis is finally conducted.

scholarly journals DETERMINING WEIGHTS OF FUZZY ATTRIBUTES FOR MULTI-ATTRIBUTE DECISION-MAKING PROBLEMS BASED ON CONSENSUS OF EXPERT OPINIONS

2015 ◽  
Vol 21 (5) ◽  
pp. 738-755 ◽  
Author(s):  
Seyed Hossein RAZAVI HAJIAGHA ◽  
Hannan Amoozad MAHDIRAJI ◽  
Shide Sadat HASHEMI ◽  
Zenonas TURSKIS
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Expert Opinions ◽  
Decision Making Problem ◽  
Order Preference ◽  
Multi Attribute Decision Making ◽  
Group Opinion ◽  
Selection Of

An important objective of a group decision-making problem is to determine the weights of attributes that are given by experts participating in the decision-making process. Since different decision-makers have unequal importance in decision-making, a series of studies focused on finding a set of appropriate weights for experts participating in a decision problem. In this paper, the problem of weight determination among decision-makers is investigated by extending an algorithm taken from the technique for order preference by similarity-to-ideal solution. In this case, a pair of most compromising and least compromising solutions is derived from individual judgments of decision-makers and then, these solutions are applied as the bases for determining the magnitude of individual alignment with the group opinion by using a closeness coefficient approach. Determining the weights of decision-makers, the group decision-making problem is then solved. Application of the proposed method is illustrated by a numerical example for the selection of a maintenance strategy.

scholarly journals TOPSIS Hybrid Multiattribute Group Decision-Making Based on Interval Pythagorean Fuzzy Numbers

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
H. U. Jun ◽  
W. U. Junmin ◽  
W. U. Jie
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Comprehensive Evaluation ◽  
Weighted Average ◽  
Decision Makers ◽  
Relative Closeness ◽  
Order Preference ◽  
Pythagorean Fuzzy Numbers

Aiming at the mixed multiattribute group decision-making problem of interval Pythagorean fuzzy numbers, a weighted average (WA) operator model based on interval Pythagorean fuzzy sets is constructed. Furthermore, a decision-making method based on the technique for order preference by similarity to ideal solution (TOPSIS) method with interval Pythagorean fuzzy numbers is proposed. First, based on the completely unknown weights of decision-makers and attributes, interval Pythagorean fuzzy numbers are applied to TOPSIS group decision-making. Second, the interval Pythagorean fuzzy number WA operator is used to synthesize the evaluation matrices of multiple decision-makers into a comprehensive evaluation matrix, and the relative closeness of each scheme is calculated based on the TOPSIS decision-making method. Finally, an example is given to illustrate the rationality and effectiveness of the proposed method.

scholarly journals An Assessment of Objectivity Convergence of Fuzzy TOPSIS Method Extended With Rank Order Weights in Group Decision Making

2018 ◽  
Vol 7 (3) ◽  
pp. 26-33
Author(s):  
Ayan Chattopadhyay ◽  
Upasana Bose
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Rank Order ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Topsis Method ◽  
Chain Management ◽  
Criteria Weights ◽  
Topsis Approach

Group decision making in a multi criteria environment is a familiar business situation where the decision makers identify an ideal choice, among many. The situation gets complex when decision makers do not have crisp data to deal with. The fuzzy TOPSIS method, and its likes, provides solution to such problems and the criteria weight plays a determinant role in the overall priority estimation. This paper presents an extended fuzzy TOPSIS approach by incorporating criteria weights derived from rank order. It considers three criteria weights; the rank order centroid, rank sum and rank reciprocal weights. The criteria weights are calculated separately and integrated with fuzzy TOPSIS method to rank choices. Finally, objectivity convergence of the alternative rankings is tested. The proposed method yields a fairly uniform and consistent result in the case of supply chain management and anticipates wide application in multi criteria environment, concomitant with uncertainty and vagueness.

A Novel Method to Assign Weights to Decision Makers for each Criterion in Group Decision Making Under Multiple Criteria with Crisp and Interval Data

2018 ◽  
Vol 5 (2) ◽  
pp. 15-46 ◽  
Author(s):  
Mohammad Azadfallah
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Interval Data ◽  
Decision Makers ◽  
Ideal Solution ◽  
Optimal Weights ◽  
Novel Method ◽  
Negative Ideal Solution ◽  
Individual Group Member

This article focuses on determining the weights of decision makers (DMs) in multi-criteria group decision making (MCGDM) environments with both crisp and interval data, in which the weights of DMs are derived from the decision matrices and DMs, have different weights for different criteria. In order to determine the optimal weights of DMs for each criterion, a new TOPSIS-based approach is introduced. In the proposed method, the DMs weight for each criterion is depends on the distances from each individual group member decision to the positive and negative ideal solution. In other words, the DM has a large weight if his/ her decision information is close (far) to the positive (negative) ideal solution, and has a small weight if his/ her decision information is far (close) from the positive (negative) ideal solution. Finally, a numerical example is given to demonstrate the feasibility of the developed methods.

Extension of the TOPSIS for Multi-Attribute Group Decision Making under Atanassov IFS Environments

2013 ◽  
pp. 241-255
Author(s):  
Deng-Feng Li ◽  
Jiang-Xia Nan
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Group Decision Making ◽  
Distance Measure ◽  
Group Decision ◽  
Intuitionistic Fuzzy Set ◽  
Ideal Solution ◽  
Euclidean Distance Measure ◽  
Order Preference ◽  
Negative Ideal Solution

This paper extends the technique for order preference by similarity to ideal solution (TOPSIS) for solving multi-attribute group decision making (MAGDM) problems under Atanassov intuitionistic fuzzy set (IFS) environments. In this methodology, weights of attributes and ratings of alternatives on attributes are extracted from fuzziness inherent in decision data and making process and described using Atanassov IFSs. An Euclidean distance measure is developed to calculate the differences between alternatives for each decision maker and an Atanassov IFS positive ideal solution (IFSPIS) as well as an Atanassov IFS negative ideal-solution (IFSNIS). Degrees of relative closeness to the Atanassov IFSPIS for all alternatives with respect to each decision maker in the group are calculated. Then all decision makers in the group may be regarded as “attributes” and a corresponding classical MADM problem is generated and hereby solved by the TOPSIS. The proposed methodology is validated and compared with other similar methods. A numerical example is examined to demonstrate the implementation process of the methodology proposed in this paper.

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