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 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.

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.

Performance Evaluation of IoT Middleware through Multicriteria Decision-Making

2018 ◽  
Author(s):  
Mauro A.A. Da Cruz ◽  
Guilherme A.B. Marcondes ◽  
Joel J. P. C. Rodrigues ◽  
Pascal Lorenz ◽  
Placido R. Pinheiro
Keyword(s):  
Decision Making ◽  
Performance Evaluation ◽  
Multicriteria Decision Making ◽  
Multicriteria Decision

A Fuzzy TOPSIS+Worst-Case Model for Personnel Evaluation Using Information Culture Criteria

2016 ◽  
Vol 7 (4) ◽  
pp. 38-66 ◽  
Author(s):  
Rasim M. Alguliyev ◽  
Ramiz M. Aliguliyev ◽  
Rasmiyya S. Mahmudova
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Topsis ◽  
Decision Makers ◽  
Personnel Evaluation ◽  
Information Culture ◽  
Worst Case ◽  
Entropy Methods ◽  
Fuzzy Mcdm

Personnel evaluation process is aimed at choosing the best alternative to fill the defined vacancy in an organization. It determines the input quality of personnel and thus plays an important role in human resource management. The multi criteria nature and the presence of qualitative factors make it considerably more complex. This paper proposes a hybrid fuzzy MCDM model for personnel evaluation. It combines the fuzzy TOPSIS method with fuzzy worst-case (or entropy) method for linguistic reasoning under group decision making. Fuzzy worst-case and entropy methods are used to get weights of criteria, while fuzzy TOPSIS is utilized to rank the alternatives. The weights obtained from fuzzy worst-case and entropy methods are included in fuzzy TOPSIS computations and the alternatives are evaluated. The fuzzy MCDM for group decision making enables to aggregate subjective assessments of the decision-makers and thus offer an opportunity to perform more robust personnel evaluation procedures. To evaluate the alternatives the authors have formed an executive group consisting of five decision-makers. For evaluation the group has decided to consider five information culture criteria expressed in linguistic variables. A numerical example demonstrated the possibilities of application of the proposed method.

Multi-Criteria Decision Making Models for Sustainable and Green Supply Chain Management Based on Fuzzy Approach

2016 ◽  
pp. 291-307 ◽  
Author(s):  
Meysam Shaverdi ◽  
Iman Ramezani ◽  
Ali Asghar Anvary Rostamy
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Business Performance ◽  
Multicriteria Decision Making ◽  
Explicit Integration ◽  
Economic Dimension ◽  
Chain Management ◽  
Decision Support Models ◽  
Fuzzy Mcdm

Understanding different aspects of sustainability, supply chain management (SCM), and decision making policies and relating them to performance measurement have been increasingly investigated in the last decade. In contrast to traditional SCM, which typically focuses on economic and financial business performance, sustainable SCM (SSCM) is characterized by explicit integration of environmental or social objectives which extend the economic dimension. For evaluating the sustainability of SCM as well as its greenness, we have to consider many and different index and criteria. One of the best tools for assessing the SSCM and GSCM is multicriteria decision making (MCDM) techniques. Many studies have been conducted in this area. Moreover, there are many uncertainty factors which may reduce the accuracy of MCDM result. Actually, Uncertainty is always a worsening factor in any decision support models, and dilutes the planned objectives of such models. For decreasing this uncertainty, fuzzy logic has been combined with MCDM approach. In fact, the main purpose of this chapter is considering the recent studies in area of SSCM and GSCM regarding to applications of fuzzy MCDM techniques. At the end of this chapter, based on out investigations in applications of fuzzy MCDM in SSCM and GSCM and regarding to research gaps, some suggestions for future studies have been proposed.

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