scholarly journals Choose Best Criteria for Decision Making Via Fuzzy Topsis Method

2017 ◽  
Vol 2 (6) ◽  
pp. 113 ◽  
Author(s):  
Muhammad Zulqarnain
Keyword(s):  
Decision Making ◽  
Fuzzy Topsis ◽  
Topsis Method

scholarly journals Evaluation of Investment Opportunities With Interval-Valued Fuzzy Topsis Method

2020 ◽  
Vol 5 (1) ◽  
pp. 461-474 ◽  
Author(s):  
Naiyer Mohammadi Lanbaran ◽  
Ercan Celik ◽  
Muhammed Yiğider
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Estimation Error ◽  
Fuzzy Topsis ◽  
Optimal Choice ◽  
Topsis Method ◽  
Relative Closeness ◽  
Ideal Solutions ◽  
Fuzzy Logic Theory ◽  
Interval Valued

AbstractThe purpose of this study is extended the TOPSIS method based on interval-valued fuzzy set in decision analysis. After the introduction of TOPSIS method by Hwang and Yoon in 1981, this method has been extensively used in decision-making, rankings also in optimal choice. Due to this fact that uncertainty in decision-making and linguistic variables has been caused to develop some new approaches based on fuzzy-logic theory. Indeed, it is difficult to achieve the numerical measures of the relative importance of attributes and the effects of alternatives on the attributes in some cases. In this paper to reduce the estimation error due to any uncertainty, a method has been developed based on interval-valued fuzzy set. In the suggested TOPSIS method, we use Shannon entropy for weighting the criteria and apply the Euclid distance to calculate the separation measures of each alternative from the positive and negative ideal solutions to determine the relative closeness coefficients. According to the values of the closeness coefficients, the alternatives can be ranked and the most desirable one(s) can be selected in the decision-making process.

scholarly journals A TWO PHASED FUZZY METHODOLOGY FOR SELECTION AMONG MUNICIPAL PROJECTS

2015 ◽  
Vol 21 (3) ◽  
pp. 405-422 ◽  
Author(s):  
Mehmet Emin BAYSAL ◽  
İhsan KAYA ◽  
Cengiz KAHRAMAN ◽  
Ahmet SARUCAN ◽  
Orhan ENGIN
Keyword(s):  
Decision Making ◽  
Fuzzy Ahp ◽  
Multicriteria Decision Making ◽  
Fuzzy Topsis ◽  
Community Life ◽  
Topsis Method ◽  
Complex Processes ◽  
Central District ◽  
Selection Of

A municipality improves the quality of community life through its projects and actions. However, project selection and prioritization by municipalities are highly complex processes. Therefore, multicriteria decision making (MCDM) methodologies are very suitable for determining the best alternative. Recently, some studies have concentrated on the selection of the best project alternatives. In this paper, a two phased fuzzy MCDM methodology is proposed for the selection among municipal projects. In the first phase, fuzzy TOPSIS method is used to select the main project group and then fuzzy AHP is used to select the best sub-municipal project. The application of the suggested methodology has been made at the central district municipality in Konya, Turkey.

scholarly journals Multi-criteria Optimization Technique with Complex Pythagorean Fuzzy N-soft Information

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Muhammad Akram ◽  
Faiza Wasim ◽  
José Carlos R. Alcantud ◽  
Ahmad N. Al-Kenani
Keyword(s):  
Decision Making ◽  
Comparative Study ◽  
Manufacturing Industry ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Fuzzy Topsis ◽  
Industrial Robots ◽  
Weighted Averaging ◽  
Topsis Method ◽  
Vikor Method

AbstractThe main objective of this article is to lay the foundations of a novel multi-criteria optimization technique, namely, the complex Pythagorean fuzzy N-soft VIKOR (CPFNS-VIKOR) method that is highly proficient to express a great deal of linguistic imprecision and vagueness inherent in human assessments. This strategy provides a versatile decision-making tool for the ranking-based fuzzy modeling of two-dimensional parameterized data. The CPFNS-VIKOR method integrates the ground-breaking specialities of the VIKOR method with the outstanding parametric structure of the complex Pythagorean fuzzy N-soft model. It is exclusively designed for the specification of a compromise optimal solution having maximum group utility and minimum individual regret of the opponent by analyzing their weighted proximity from ideal solutions. The developed strategy factually permits specific linguistic terms to demystify the individual perspectives of the decision-making experts regarding the efficacy of the alternatives and the priorities of the applicable criteria. We comprehensively assemble these independent appraisals of all the experts using the complex Pythagorean fuzzy N-soft weighted averaging operator. Moreover, we calibrate the ranking measure by utilizing group utility measure and regret measure in order to specify the hierarchical outranking of the feasible alternatives. We demonstrate the systematic methodology and framework of the proposed method with the assistance of an explicative flow chart. We skilfully investigate an empirical analysis related to selection of constructive industrial robots for the modernization of a manufacturing industry which really justifies the remarkable accountability of the proposed strategy. Furthermore, we validate this technique by a comparative study with the existing complex Pythagorean fuzzy TOPSIS (CPF-TOPSIS) method, complex Pythagorean fuzzy VIKOR (CPF-VIKOR) method and Pythagorean fuzzy TOPSIS (PF-TOPSIS) method. The comparative study is exemplified with an illustrative bar chart that visually endorses the rationality of the proposed methodology by interpreting highly compatible and accurate final outcomes. Finally, we holistically analyze the functionality of the developed strategy to enlighten its merits and prominence over other available competent approaches.

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.

scholarly journals Picture Fuzzy TOPSIS Method Based on CPFRS Model: An Application to Risk Management Problems

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Jiulin Jin ◽  
Ping Zhao ◽  
Taijie You
Keyword(s):  
Decision Making ◽  
Risk Management ◽  
Multicriteria Decision Making ◽  
Fuzzy Topsis ◽  
Green Buildings ◽  
Topsis Method ◽  
Fuzzy Rough Set ◽  
Established Method ◽  
Logical Operators ◽  
Wide Range

It is not widely acknowledged that multicriteria decision-making (MCDM) problems in some particular circumstances cannot be effectively solved by some traditional methods. This paper aims to construct a novel decision-making method to effectively solve these MCDM problems. Firstly, we propose a covering-based picture fuzzy rough set (CPFRS) model by combining the picture fuzzy (PF) neighborhood operator and some PF logical operators. Secondly, by combining the proposed CPFRS model with the principle of TOPSIS method, a new method is proposed to solve the MCDM problems under PF environments. Finally, we apply our proposed method to the risk management of green buildings. By comparing the proposed method with some existing MCDM methods, the established method is effective and flexible and can be applied to a wide range of environments.

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