A New Method for Ranking Triangular Fuzzy Numbers

Akyar, Emrah; Akyar, Handan; Düzce, Serkan Ali

doi:10.1142/s021848851250033x

Cited by 43 publications

(31 citation statements)

References 12 publications

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“…To select the most preferred alternatives, standard approaches to comparing fuzzy numbers [21,22] can then be applied.…”

Section: Application Example Of the Modified Mavt Methodsmentioning

confidence: 99%

Decision-Making Based on Multi-Attribute Value Theory Under Preference Uncertainty

Shakirov¹

2019

Proceedings of the 7th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2019)

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This paper advances the multi-attribute value theory to take into account the uncertainty of the decisionmaker's preferences with respect to the value of assessments and importance of attributes. It considers the basic steps of the original method of multi-attribute value theory against the modified one. The modified method can use the decisionmaker's responses as fuzzy triangular numbers to construct single-attribute value functions and to find the scaling coefficients. The paper presents an approach to finding fuzzy scaling coefficients by comparing paired matches and generating a system of linear equations with fuzzy coefficients. It is proposed to solve the system of equations by representing it as a set of systems of interval equations derived by splitting fuzzy sets by α levels. Multi-attribute fuzzy assessment of alternatives is carried out by solving linear programming problems based on systems of equations pertaining to individual α levels. The paper provides an example of using the modified method for multi-attribute comparison of alternatives.

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“…To select the most preferred alternatives, standard approaches to comparing fuzzy numbers [21,22] can then be applied.…”

Section: Application Example Of the Modified Mavt Methodsmentioning

confidence: 99%

Decision-Making Based on Multi-Attribute Value Theory Under Preference Uncertainty

Shakirov¹

2019

Proceedings of the 7th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2019)

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“…A fuzzy set M on a set X is a function M: X [0,1]. A type of fuzzy number that can better match with real-life applications is a triangular fuzzy number [44,45]. This type of fuzzy number has a triangle-shaped membership function, as shown in Figure 1.…”

Section: Triangular Fuzzy Number (Tfn)mentioning

confidence: 99%

Development of an Assessment Method for Evaluation of Sustainable Factories

et al. 2020

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The role of the industrial sector in total greenhouse gas (GHG) emissions and resource consumption is well-known, and many industrial activities may have a negative environmental impact. The solution to decreasing the negative effects cannot be effective without the consideration of sustainable development. There are several methods for sustainability evaluation, such as tools based on products, processes, or plants besides supply chain or life cycle analysis, and there are different rating systems suggesting 80, 140, or more indicators for assessment. The critical point is the limits such as required techniques and budget in using all indicators for all factories in the beginning. Moreover, the weight of each indicator might change based on the selected alternative that it is not a fixed value and could change in a new case study. In this regard, to determine the impact and weight of different indicators in sustainable factories, a multi-layer Triangular Fuzzy Analytic Hierarchy Process (TFAHP) approach was developed, and the application of the method was described and verified. The defined layers are six; for each layer, the pairwise comparison matrix was developed, and the total aggregated score concerning the sustainability goal for each alternative was calculated that shows the Relative Importance Coefficient (RIC). The method is formulated in a way that allows adding the new indicators in all layers as the verification shows, and thus, there are no limits for using any green rating systems. Therefore, the presented approach by TFAHP would provide an additional tool toward the sustainable development of factories.

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“…Calculate the fuzzy weight sector of FCMs. In the weight decision analysis, the cut set of fuzzy analysis is used to remove the fuzziness of the weight (E. Akyar, H. Akyar, & Duzce, 2012). The following assumptions are made:…”

Section: Weightsmentioning

confidence: 99%

Fanpce Technique for Risk Assessment on Subway Station Construction

Bai

Che

et al. 2019

Journal of Civil Engineering and Management

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Risk assessment is critical for the construction of the subway station to improve the risk management and reduce the additional loss. According to field investigation of safe construction, the analytical network process (ANP), fuzzy set theory and fuzzy comprehensive evaluation (FCE), a fuzzy ANP comprehensive evaluation (FANPCE) model was proposed to evaluate the risk of subway station construction in this paper. Twelve key risk factors of subway station construction were identified through literature review and questionnaires. The interdependency among risk factors were illustrated through the network structure of ANP, and then a weight matrix of single risk factors was built by comments and survey results, and the interdependent weight matrix was quantified by integrating the triangular fuzzy number into the ANP. Subsequently, the total risk rank of assessed projects can be quantified though the synthesis of weight matrices with the synthetic operator of FCE. Wu Lu Kou subway station was selected as a case study. The results imply that, construction experience, underground water, and safety consciousness have a substantial influence on construction projects and that the total construction risk of Wu Lu Kou subway station is ranked at I level. Moreover, the loss analysis of the whole construction process verifies this method. This research contributes to developing a FANPCE method to identify the risk factors with high weights, assess the risk rank of projects and appropriately respond to the results. In addition, the developed fuzzy set theory-ANP-FCE integrated network provides stakeholders a consolidated model for the risk evaluation.

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A New Method for Ranking Triangular Fuzzy Numbers

Cited by 43 publications

References 12 publications

Decision-Making Based on Multi-Attribute Value Theory Under Preference Uncertainty

Decision-Making Based on Multi-Attribute Value Theory Under Preference Uncertainty

Development of an Assessment Method for Evaluation of Sustainable Factories

Fanpce Technique for Risk Assessment on Subway Station Construction

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