Models and methods of decision making in fuzzy environment and their applications to power engineering problems

2007 ◽  
Vol 14 (4) ◽  
pp. 369-390 ◽  
Author(s):  
L. Canha ◽  
P. Ekel ◽  
J. Queiroz ◽  
F. Schuffner Neto
2011 ◽  
Vol 33 (3) ◽  
pp. 623-632 ◽  
Author(s):  
R.C. Berredo ◽  
P.Ya. Ekel ◽  
J.S.C. Martini ◽  
R.M. Palhares ◽  
R.O. Parreiras ◽  
...  

2016 ◽  
Vol 361-362 ◽  
pp. 100-119 ◽  
Author(s):  
Petr Ekel ◽  
Illya Kokshenev ◽  
Roberta Parreiras ◽  
Witold Pedrycz ◽  
Joel Pereira Jr.

Author(s):  
Syed Abou Iltaf Hussain ◽  
Sankar Prasad Mondal ◽  
Uttam Kumar Mandal

Multi-Criteria Decision Making has evolved as an important tool for taking some of the most important decisions in the today's hi-tech engineering world. But due to some reasons like measurement difficulty, lack of data, faulty instruments, etc., or due to lack of absolute information about the topic, alternatives present and the criteria, decision making becomes very difficult as all parameter for modeling a decision making problem are not precise. In such scenario the importance of one with respect to the others are represented in terms of linguistic factor. Such cases could be tackled by considering the problem in fuzzy environment. In this chapter, the different hybrid fuzzy MCDM techniques are shown along with their application in different engineering problems. One problem is randomly selected and solved using different fuzzy MCDM techniques and compared the result with the existing literature.


Engineering ◽  
2013 ◽  
Vol 05 (05) ◽  
pp. 41-51 ◽  
Author(s):  
Petr Ya. Ekel ◽  
Illya V. Kokshenev ◽  
Roberta O. Parreiras ◽  
Gladstone B. Alves ◽  
Paulo M. N. Souza

2021 ◽  
pp. 1-18
Author(s):  
Xiang Jia ◽  
Xinfan Wang ◽  
Yuanfang Zhu ◽  
Lang Zhou ◽  
Huan Zhou

This study proposes a two-sided matching decision-making (TSMDM) approach by combining the regret theory under the intuitionistic fuzzy environment. At first, according to the Hamming distance of intuitionistic fuzzy sets and regret theory, superior and inferior flows are defined to describe the comparative preference of subjects. Hereafter, the satisfaction degrees are obtained by integrating the superior and inferior flows of the subjects. The comprehensive satisfaction degrees are calculated by aggregating the satisfaction degrees, based on which, a multi-objective TSMDM model is built. Furthermore, the multi-objective TSMDM model is converted to a single-objective model, the optimal solution of the latter is derived. Finally, an illustrative example and several analyses are provided to verify the feasibility and the effectiveness of the proposed approach.


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