scholarly journals Supportiveness of Low-Carbon Energy Technology Policy Using Fuzzy Multicriteria Decision-Making Methodologies

Mathematics ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 1178 ◽  
Author(s):  
Konstantinos Kokkinos ◽  
Vayos Karayannis
Keyword(s):  
Decision Making ◽  
Swot Analysis ◽  
Technology Policy ◽  
Multicriteria Decision Making ◽  
Clean Energy ◽  
Policy Formulation ◽  
Ideal Solution ◽  
Low Carbon ◽  
Multicriteria Decision ◽  
Low Carbon Energy

The deployment of low-carbon energy (LCE) technologies and management of installations represents an imperative to face climate change. LCE planning is an interminable process affected by a multitude of social, economic, environmental, and health factors. A major challenge for policy makers is to select a future clean energy strategy that maximizes sustainability. Thus, policy formulation and evaluation need to be addressed in an analytical manner including multidisciplinary knowledge emanating from diverse social stakeholders. In the current work, a comparative analysis of LCE planning is provided, evaluating different multicriteria decision-making (MCDM) methodologies. Initially, by applying strengths, weaknesses, opportunities, and threats (SWOT) analysis, the available energy alternative technologies are prioritized. A variety of stakeholders is surveyed for that reason. To deal with the ambiguity that occurred in their judgements, fuzzy goal programming (FGP) is used for the translation into fuzzy numbers. Then, the stochastic fuzzy analytic hierarchical process (SF-AHP) and fuzzy technique for order performance by similarity to ideal solution (F-TOPSIS) are applied to evaluate a repertoire of energy alternative forms including biofuel, solar, hydro, and wind power. The methodologies are estimated based on the same set of tangible and intangible criteria for the case study of Thessaly Region, Greece. The application of FGP ranked the four energy types in terms of feasibility and positioned solar-generated energy as first, with a membership function of 0.99. Among the criteria repertoire used by the stakeholders, the SF-AHP evaluated all the criteria categories separately and selected the most significant category representative. Finally, F-TOPSIS assessed these criteria ordering the energy forms, in terms of descending order of ideal solution, as follows: solar, biofuel, hydro, and wind.

Fuzzy multicriteria decision-making-based optimal Zn–Al alloy selection in corrosive environment

2020 ◽  
Vol 111 (11) ◽  
pp. 953-963
Author(s):  
Ankur V. Bansod ◽  
Awanikumar P. Patil ◽  
Kanak Kalita ◽  
B. D. Deshmukh ◽  
Nilay Khobragade
Keyword(s):  
Decision Making ◽  
Weight Loss ◽  
Multicriteria Decision Making ◽  
Decision Makers ◽  
Al Alloy ◽  
Ideal Solution ◽  
Corrosive Environment ◽  
Multicriteria Decision ◽  
Al Content ◽  
The Ideal

Abstract Suitable material selection with emphasis on a specific property or application is an indispensable part of engineering sciences. It is a complex process that involves multiple criteria and often multiple decision makers. The tendency of decision makers to specify their preference in terms of imprecise qualitative statements like ‘good’, ‘bad’ etc. poses a further challenge. Thus, in this research, a comprehensive multicriteria decision-making study was conducted to select the optimal Zn-Al alloy based on performance in a corrosive environment. Four variants of technique for order of preference by similarity to the ideal solution were used to perform the multicriteria decision-making analysis. Group decision and imprecise decision making is handled by incorporating the fuzzy theory concept in a technique for order of preference by similarity to the ideal solution. The effect of addition of aluminium to zinc was studied by examination of microstructure, hardness, and corrosion behaviour. The result indicates that an increase in Al content increases the formation of dendrites. The dendrites were rich in the α phase, which results in an increase in hardness. An increase in Al content in Zn (Zn-22Al and Zn-55Al) results in the uniform distribution of the a phase in the microstructure and reduction of non-equilibrium phases. The potentiodynamic polarisation test revealed that an increase in Al in the alloy decreases the corrosion current density. The weight loss test carried out to validate the potentiodynamic test findings exhibited higher weight loss in pure Zn and lowest in Zn-55Al. Similar results were observed in the salt spray test. The multicriteria decision-making analysis revealed that Zn-55Al is the most suitable alloy in a corrosive environment among the tested alloys.

scholarly journals A Study of Multicriteria Decision Making for Supplier Selection in Automotive Industry

2013 ◽  
Vol 2013 ◽  
pp. 1-22 ◽  
Author(s):  
Nadia Jamil ◽  
Rosli Besar ◽  
H. K. Sim
Keyword(s):  
Decision Making ◽  
Analytical Hierarchy Process ◽  
Supplier Selection ◽  
Selection Process ◽  
Multicriteria Decision Making ◽  
Ideal Solution ◽  
Fuzzy Analytical Hierarchy Process ◽  
Automotive Manufacturing ◽  
Multicriteria Decision ◽  
Hierarchy Process

This paper is designed to present the effectiveness of group multicriteria decision making in automotive manufacturing company focusing on the selection of suppliers in Malaysia. The process of selecting suppliers is one of the most critical and challenging endeavor in any supply chain management. There are five decision making tools being analyzed in this study, namely, analytical hierarchy process (AHP), fuzzy analytical hierarchy process (FAHP), technique for order performance by similarity to ideal solution (TOPSIS), fuzzy technique for order performance by similarity to ideal solution (FTOPSIS), and fuzzy analytical hierarchy process integrated with fuzzy technique for order performance by similarity to ideal solution (FAHPiFTOPSIS). The scores of ranking among the suppliers in each MCDM tools (AHP, FAHP, TOPSIS, FTOPSIS, and FAHPiFTOPSIS) show significantly comparable variation. Scores of the best supplier is then compared to the lowest supplier for all MCDM tools whereby this reflects that the highest percentage goes to TOPSIS with scoring of 79.37%. On the contrary, FAHPiFTOPSIS demonstrated the lowest score variation of 22.42% which indicates that FAHPiFTOPSIS is able to eliminate biasness in supplier selection process.

scholarly journals A Fuzzy-Grey Multicriteria Decision Making Approach for Green Supplier Selection in Low-Carbon Supply Chain

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Qinghua Pang ◽  
Tiantian Yang ◽  
Mingzhen Li ◽  
Yi Shen
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Supplier Selection ◽  
Multicriteria Decision Making ◽  
Low Carbon ◽  
Chain Management ◽  
Multicriteria Decision ◽  
Green Supplier Selection ◽  
Carbon Supply

Due to the increasing awareness of global warming and environmental protection, many practitioners and researchers have paid much attention to the low-carbon supply chain management in recent years. Green supplier selection is one of the most critical activities in the low-carbon supply chain management, so it is important to establish the comprehensive criteria and develop a method for green supplier selection in low-carbon supply chain. The paper proposes a fuzz-grey multicriteria decision making approach to deal with these problems. First, the paper establishes 4 main criteria and 22 subcriteria for green supplier selection. Then, a method integrating fuzzy set theory and grey relational analysis is proposed. It uses the membership function of normal distribution to compare each supplier and uses grey relation analysis to calculate the weight of each criterion and improves fuzzy comprehensive evaluation. The proposed method can make the localization of individual green supplier more objectively and more accurately in the same trade. Finally, a case study in the steel industry is presented to demonstrate the effectiveness of the proposed approach.

scholarly journals A Hybrid Fuzzy Analytic Hierarchy Process and the Technique for Order of Preference by Similarity to Ideal Solution Supplier Evaluation and Selection in the Food Processing Industry

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 211 ◽  
Author(s):  
Chia-Nan Wang ◽  
Hsiung-Tien Tsai ◽  
Van Thanh Nguyen ◽  
Viet Tinh Nguyen ◽  
Ying-Fang Huang
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Vegetable Oil ◽  
Multicriteria Decision Making ◽  
Fuzzy Analytic Hierarchy Process ◽  
Supplier Evaluation ◽  
Ideal Solution ◽  
Analytic Hierarchy ◽  
Multicriteria Decision ◽  
Hierarchy Process

Selecting suppliers plays an important role in improving efficiency of supply chains. In the field of extraction of vegetable oil, one of the main submaterials is hexane solvent. Choosing a supplier of hexane solvent is a multicriteria decision-making task that decision-makers must have an understanding of the quantitative and qualitative elements for assessing the symmetrical impact of the criteria to reach the most accurate result. In this paper, the authors suggest a multicriteria decision-making (MCDM) model for N-hexane solvent (C6H14) supplier evaluation and selection for vegetable oil production. All criteria affecting to the hexane solvent supplier evaluation and selection process are defined by experts. Then, a fuzzy analytic hierarchy process (FAHP) multicriteria comparative analysis method has been applied for determining the weight of all criteria. Finally, the technique for order of preference by similarity to ideal solution (TOPSIS) was applied to select the optimal hexane solvent supplier. As a result, decision making unit 003 (DMU3) is the optimal supplier. The contribution of this research is to propose an MCDM model for hexane solvent supplier selection in the food industry. The work also proposed a useful guideline for supplier evaluation and selection processes in other industries.

scholarly journals A Novel Dynamic Multicriteria Decision-Making Approach for Low-Carbon Supplier Selection of Low-Carbon Buildings Based on Interval-Valued Triangular Fuzzy Numbers

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Xia Cao ◽  
Zeyu Xing ◽  
Yuqi Sun ◽  
Shi Yin
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Construction Projects ◽  
Comprehensive Evaluation ◽  
Multicriteria Decision Making ◽  
Building Construction ◽  
Low Carbon ◽  
Multicriteria Decision ◽  
Interval Valued ◽  
Selection Of

Due to the lack of natural resources and environmental problems which have been appearing increasingly, low-carbon buildings are more and more involved in the construction industry. The selection of low-carbon supplier is a significant part in the process of low-carbon building construction projects. In this paper, we propose a novel dynamic multicriteria decision-making approach for low-carbon supplier selection in the process of low-carbon building construction projects to deal with these problems. First, the paper establishes 5 main criteria and 17 subcriteria for low-carbon supplier selection in the process of low-carbon building construction projects. Then, a method considering interaction between criteria and the influence of constructors subjective preference and objective criteria information is proposed. It uses the basic concept and properties of the interval-valued triangular fuzzy number intuitionistic fuzzy weighted Bonferroni means (IVTFNIFWBM) operators and the objective information entropy and TOPSIS-based Euclidean distance to calculate the comprehensive evaluation results of potential low-carbon suppliers. The proposed method is much easier for constructors to select low-carbon supplier and make the localization of low-carbon supplier more practical and accurate in the process of building construction projects. Finally, a case study about a low-carbon building project is given to verify practicality and effectiveness of the proposed approach.

scholarly journals EVALUATION OF FINANCIAL PERFORMANCES OF SME’S LISTED IN THE BIST SME INDUSTRIAL INDEX BY USING TOPSIS MULTICRITERIA DECISION MAKING METHOD

2020 ◽  
Vol 9 (3) ◽  
pp. 63
Author(s):  
Selcuk Kendirli ◽  
Muhammet Selcuk Kaya ◽  
Mustafa Bilgin
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Total Employment ◽  
Multicriteria Decision ◽  
Statistical Institute ◽  
Ideal Solutions ◽  
Order Preference ◽  
Negative Ideal Solution

In this study, the financial performances of SMEs listed in the BIST SME Industrial Index are evaluated by using TOPSIS multicriteria decision-making method. The data of the study acquired from annual financial statements that reported between the 2016-2018 period. Financial performance ranks of SMEs are determined for each year and thus comparative financial performances of SMEs are detected.BIST SME Industrial Index is an index that includes stocks of industrial SMEs traded in BIST Stars, BIST Main, and BIST Emerging Companies markets. SMEs have great importance for the Turkish economy, with their dynamizing roles and with their crucial roles in regional development and job creation. According to the Turkey Statistical Institute data, Turkish SMEs constitute 99.8 % of all enterprises in Turkey. At the same time, Turkish SMEs provide 72.7% of total employment, 62% of total sales, and 58% of the total investments of the Turkish Economy.Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is one of the multicriteria decision-making methods that commonly used in the evaluation of financial performances of firms. The TOPSIS method is based on two main points: the positive ideal solution and the negative ideal solution. With the help of the TOPSIS method, the distances positive ideal solutions and negative ideal solutions of all options are calculated. Options are ranked according to their proximity to the positive ideal solution and their distance to the negative ideal solution. 

scholarly journals Closeness Degree-Based Hesitant Trapezoidal Fuzzy Multicriteria Decision Making Method for Evaluating Green Suppliers with Qualitative Information

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Xiaolu Zhang ◽  
Touping Yang ◽  
Wei Liang ◽  
Meifang Xiong
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Food Supply ◽  
Multicriteria Decision Making ◽  
Ideal Solution ◽  
Qualitative Information ◽  
Food Supply Chain ◽  
Complete Evaluation ◽  
Multicriteria Decision ◽  
Green Suppliers

The aim of this study is to develop a new closeness degree-based hesitant trapezoidal fuzzy (HTrF) multicriteria decision making (MCDM) approach for identifying the most appropriate green suppliers in food supply chain involving uncertain qualitative evaluation information. The uniqueness of the proposed HTrF MCDM method is the consideration of uncertain qualitative information represented by flexible linguistic expressions based on HTrF values and the construction of compromise solution with the revised closeness degree. The revised closeness degree can make sure that the most appropriate solution has the shortest distance from the HTrF positive ideal solution and the farthest distance from the HTrF negative ideal solution, simultaneously. This proposed HTrF MCDM technique not only offers a simple and efficient decision support tool to aid the food firms for identifying the optimal suppliers in food supply chain but also can enable the managers of food firms to better understand the complete evaluation and decision processes. In addition, this study provides a novel defuzzification technique to manage the HTrF weights values of main-criteria and subcriteria, respectively.

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