The Evaluation of Renewable Energy Technologies for Electricity Generation in Turkey Using Intuitionistic Fuzzy TOPSIS

Boran, Fatih Emre; Boran, Kurtuluş; Menlik, Tayfun

doi:10.1080/15567240903047483

Cited by 155 publications

(68 citation statements)

References 42 publications

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“…, C n } be a set of criteria. It should be mentioned here that the presented approach mainly utilizes the IFT method proposed in [39,[42][43][44]48]. The procedure for AHP-IFT methodology is conducted in seven steps presented as follows: Step 1 Determine the weight of the criteria based on the opinion of decision-makers (W).…”

Section: Ahp-ift Hybrid Methodsmentioning

confidence: 99%

AHP and Intuitionistic Fuzzy TOPSIS Methodology for SCM Selection

Rouyendegh

2014

Advanced Business Analytics

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Section: Ahp-ift Hybrid Methodsmentioning

confidence: 99%

AHP and Intuitionistic Fuzzy TOPSIS Methodology for SCM Selection

Rouyendegh

2014

Advanced Business Analytics

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“…4 In the last decades, a lot of methods have been proposed to deal with group decision making under di®erent environments. [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22] From another point of view, according to the information about the weight vectors of the criteria or the decision makers, group decision-making problems fall into two categories: the one with the weight vector known and the one with the weight vector incompletely known which also contains the one with the weight vector completely unknown. For the¯rst class, the research topics focus on investigating aggregation techniques, and various ones have been developed, such as the ordered weighted averaging operator, 23 the ordered weighted geometric operator, 24,25 the power averaging operator, 26,27 the Boferroni mean, 13,28,29 which are used to aggregate the original decision information.…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for Fuzzy Multi-Criteria Decision Making

Mao

Zhang

2014

Int. J. Info. Tech. Dec. Mak.

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To determine the weight vector and to aggregate the individual opinions are necessary steps in the classical methods for multi-criteria group decision-making problems in which the weight vectors of the decision makers and the criteria are incompletely known. In this paper, we propose a simple but e±cient approach which can avoid these steps by establishing some optimal models. To get the optimal group decision matrix, we¯rst propose two kinds of models among which the former focuses on minimizing the deviations between individual decision matrix and the ideal group one, while the latter aims at minimizing the deviations between the estimated group opinion and the ideal group one. To get the overall performances of alternatives, another two types of models are further established, one of which is to minimize the distance between the evaluation value under each criterion and the ideal overall value for each alternative, and the other is to minimize the distance between the estimated overall value and the ideal overall one. The proposed models can be used to deal with group decision-making under intuitionistic fuzzy, interval-valued fuzzy or other fuzzy environments, and can also provide the decision makers more choices by containing the parameter which can be assigned di®erent values according to di®erent actual situations. Several examples illustrate the practicability of the proposed methods.

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“…For instance, in supply chain management and logistics, the TOPSIS approach was used for supplier selection (Chen et al, 2006;Boran et al, 2009;Celik, 2010;Chen, 2011;Dalalah et al, 2011;Deng and Chan, 2011;Fazlollahtabar et al, 2011), the location problem (Chu, 2002;Yong, 2006;Ertuğrul, 2010;Kuo, 2011;Awasthi et al, 2011;Li et al, 2011) and the selecting service problems (Bottani and Rizzi, 2006;Kahraman et al, 2007;Lin and Tsai, 2009;Chamodrakas et al, 2011;Cheng et al, 2011). It was also used in energy management (Yan et al, 2011;Kaya and Kahraman, 2011;Boran et al, 2012), chemical engineering (Rao and Baral, 2011;Sun et al, 2011;Ramezani et al, 2011), health problem (Rahimi et al, 2007;Wang et al, 2010;La Scalia et al, 2011) and even for the new ground-air missile weapon system selection problem (Li et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

The Characteristic Objects Method: A New Distance‐based Approach to Multicriteria Decision‐making Problems

Sałabun

2014

Multi Criteria Decision Anal

143

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Multicriteria decision-making (MCDM) methods are concerned with the ranking of alternatives based on expert judgements made using a number of criteria. In the MCDM field, the distance-based approach is one popular method for obtaining a final ranking. The technique for order preference by similarity to the ideal solution (TOPSIS) is a commonly used example of this kind of MCDM method. The TOPSIS ranks the alternatives with respect to their geometric distance from the positive and negative ideal solutions. Unfortunately, two reference points are often insufficient, especially for nonlinear problems. As a consequence of this situation, the final result ranking is prone to errors, including the rank reversals phenomenon.This study proposes a new distance-based MCDM method: the characteristic objects method. In this approach, the preferences of each alternative are obtained on the basis of the distance from the nearest characteristic objects and their values. For this purpose, we have determined the domain and Fuzzy number set for all the considered criteria. The characteristic objects are obtained as the combination of the crisp values of all the Fuzzy numbers. The preference values of all the characteristic object are determined on the basis of the tournament method and the principle of indifference. Finally, the Fuzzy model is constructed and is used to calculate preference values of the alternatives, making it a multicriteria model that is free of rank reversal. The numerical example is used to illustrate the efficiency of the proposed method with respect to results from the TOPSIS method. The characteristic objects method results are more realistic than the TOPSIS results.

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The Evaluation of Renewable Energy Technologies for Electricity Generation in Turkey Using Intuitionistic Fuzzy TOPSIS

Cited by 155 publications

References 42 publications

AHP and Intuitionistic Fuzzy TOPSIS Methodology for SCM Selection

AHP and Intuitionistic Fuzzy TOPSIS Methodology for SCM Selection

A Novel Method for Fuzzy Multi-Criteria Decision Making

The Characteristic Objects Method: A New Distance‐based Approach to Multicriteria Decision‐making Problems

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