scholarly journals Prioritization in Strategic Environmental Assessment Using Fuzzy TOPSIS Method with Random Generation for Absent Information in South Korea

2021 ◽  
Vol 13 (3) ◽  
pp. 1458
Author(s):  
Daeryong Park ◽  
Huan-Jung Fan ◽  
Jun-Jie Zhu ◽  
Taesoon Kim ◽  
Myoung-Jin Um ◽  
...  
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Fuzzy Topsis ◽  
River Basins ◽  
Ideal Solution ◽  
Missing Information ◽  
Nakdong River ◽  
Han River ◽  
Priority Ranking ◽  
The Nakdong River

This study evaluated a fuzzy technique for order performance by similarity to ideal solution (TOPSIS) as a multicriteria decision making system that compensates for missing information with undefined weight factor criteria. The suggested Fuzzy TOPSIS was applied to ten potential dam sites in three river basins (the Han River, the Geum River, and the Nakdong River basins) in South Korea. To assess potential dam sites, the strategic environment assessment (SEA) monitored four categories: national preservation, endangered species, water quality, and toxic environment. To consider missing information, this study applied the Monte Carlo Simulation method with uniform and normal distributions. The results show that effects of missing information generation with one fuzzy set in GB1 site of the Geum River basin are not great in fuzzy positive-ideal solution (FPIS) and fuzzy negative-ideal solution (FNIS) estimations. However, the combination of two fuzzy sets considering missing information in Gohyun stream (NG) and Hoenggye stream (NH) sites of the Nakdong River basin has a great effect on estimating FPIS, FNIS, and priority ranking in Fuzzy TOPSIS applications. The sites with the highest priority ranking in the Han River, Geum River, and Nakdong River basins based on Fuzzy TOPSIS are the Dal stream 1 (HD1), Bocheong stream 2 (GB2) and NG sites. Among the sites in all river basins, the GB2 site had the highest priority ranking. Consequently, the results coincided with findings of previous studies based on multicriteria decision making with missing information and show the applicability of Fuzzy TOPSIS when evaluating priority rankings in cases with missing information.

scholarly journals Evaluating Olympic Pictograms Using Fuzzy TOPSIS – Focus on Judo, Taekwondo, Boxing, and Wrestling

2021 ◽  
Author(s):  
Choi kyoungho ◽  
Kim Bongseok ◽  
Jinhee Choi
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Fuzzy Topsis ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Weight Changes ◽  
Beijing Olympics ◽  
Priority Ranking ◽  
The Ideal

This study evaluated the ranking of comprehensibility of the pictograms for judo, taekwondo, boxing, and wrestling used in the six games from the 27th Sydney Olympics in 2000 to the 32nd Tokyo Olympics in 2021. The evaluation was done using the Fuzzy TOPSIS method, one of the multi-criteria decision-making methodologies commonly used in economics and others fields. The results are as follows. The first, pictograms from the 2008 Beijing Olympics ranked first in three sports: taekwondo, boxing, and wrestling, but there were no pictograms that consistently ranked first or sixth in all sports. Second, the result of the sensitivity analysis shows a possibility that the ranking will be reversed if the weight of the evaluation factors changes, but in the 1000-time repetitive prediction, the better the evaluation ranking, the closer the value of the priority ranking to the ideal solution on average even if the weight changes.

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.

Fuzzy Multicriteria Decision Making Methodologies Used in the Book

2020 ◽  
pp. 92-131
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Fuzzy Topsis ◽  
Suitable Model ◽  
Fuzzy Dematel ◽  
Multicriteria Decision ◽  
Fuzzy Vikor

Using an appropriate methodology is crucial in the analysis. Therefore, the suitable model should be selected according to the type of the evaluation. Otherwise, there is a risk of having inappropriate results. Because of this situation, recommendations can be problematic. In this book, three different analyses are performed. In two of them, fuzzy DEMATEL, fuzzy TOPSIS, and fuzzy VIKOR approaches are taken into consideration. In this chapter, these three methods are explained. In this framework, some studies, which used these methods, are explained.

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 Comparative Study between GLP and GBWM

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Reda M. S. Abdulaal ◽  
Omer A. Bafail
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Comparative Study ◽  
Simplex Method ◽  
Multicriteria Decision Making ◽  
Decision Makers ◽  
The Other ◽  
Ideal Solution ◽  
Linguistic Variables ◽  
Best Worst Method

When decision-makers’ judgments are uncertain, they often express their opinions using grey linguistic variables. Once used, the data often retains its grey nature throughout all subsequent decision-making iterations. Multicriteria decision-making (MCDM) is a tool used when making complicated decisions and in circumstances where several criteria require evaluation to choose the most desirable option. Grey data serves as the basis for several MCDM methods. This paper compares two MCDM methods, Grey-Linear-Programming (GLP) and Grey-Best-Worst-Method (GBWM), in terms of the weights of decision criteria and their rankings. Moreover, Grey-The Technique for Order of Preference by Similarity to Ideal Solution (GTOPSIS) was used to rank the weights of the two methods. Study findings demonstrated that GBWM requires more mathematical calculations than GLP, based on linear programming's classic simplex method. On the other hand, when GTOPSIS follows GLP, the alternative rank does not change compared to when GTOPSIS followed GBWM. For the applications used in this comparison, GLP procedure is considered simpler than GBWM procedure.

scholarly journals A Hybrid Novel Fuzzy MCDM Method for Comprehensive Performance Evaluation of Pumped Storage Power Station in China

Mathematics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 71
Author(s):  
Peipei You ◽  
Sijia Liu ◽  
Sen Guo
Keyword(s):  
Decision Making ◽  
Performance Evaluation ◽  
Multicriteria Decision Making ◽  
Fuzzy Topsis ◽  
Power Station ◽  
Power Stations ◽  
Comprehensive Performance ◽  
Mcdm Method ◽  
Fuzzy Mcdm ◽  
Pumped Storage

Considering the goals of carbon peaking and carbon neutrality, along with their related policies, pumped storage power stations are set to develop quickly in China. The comprehensive performance of pumped storage power stations must urgently be evaluated, which can help investors in decision making and provide a reference for policymakers. In this paper, a hybrid novel fuzzy multicriteria decision-making (MCDM) method combining the fuzzy best worst method (BWM) and fuzzy TOPSIS was proposed for the comprehensive performance evaluation of pumped storage power stations in China. The fuzzy BWM was utilized to determine the criteria weights describing the comprehensive performance of pumped storage power stations, while the fuzzy TOPSIS was used to rank the comprehensive performance of pumped storage power stations. The index system for the comprehensive performance evaluation of pumped storage power stations in China incorporated economic, social, and environmental aspects. The comprehensive performance of four pumped storage power stations in China was empirically evaluated using the proposed hybrid novel fuzzy MCDM method, and the results indicate that pumped storage power station PSPS2 exhibited the best comprehensive performance, followed by pumped storage power stations PSPS1 and PSPS4, whereas pumped storage power station PSPS3 had the worst comprehensive performance. A sensitivity analysis and comparative analysis were also conducted. The results indicate that the proposed hybrid novel fuzzy MCDM method, combining the fuzzy BWM and fuzzy TOPSIS for comprehensive performance evaluation of pumped storage power stations, is robust and effective.

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.

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