Title of article :
Sustainable Energy Planning By A Group Decision Model With Entropy Weighting Method Under Interval-Valued Fuzzy Sets an‎d Possibilistic Statistical Concepts
Author/Authors :
Foroozesh, Nazanin Department of Industrial Engineering and Management Systems - Amirkabir University of Technology, Tehran , Karimi, Behrooz Department of Industrial Engineering and Management Systems - Amirkabir University of Technology, Tehran , Mirzaei, Ehsan Department of Industrial Engineering - Faculty of Engineering - Shahed University, Tehran
Pages :
14
From page :
99
To page :
112
Abstract :
In this paper, a new interval-valued fuzzy multi-criteria group decision-making model is proposed to evaluate each of the energy plans with sustainable development criteria for proper energy plan selection. The purpose of this study is divided into two parts: first, it is aimed at determining the weights of evaluation criteria for sustainable energy planning and second at rating sustainable energy alternatives by a group decision model under uncertainty. In the proposed method, given the concept of asymmetric data, possibilistic statistical concepts are used to make a more appropriate decision with less uncertainty consideration. A new rating system based on the reference point and a new improved version of Entropy method are introduced as the leading features of this model to determine the weight of criteria and possibilistic statistical concepts, including mean, standard deviation and cube root of skewness in the interval-valued fuzzy form, by considering positive and negative ideal points. Moreover, a practical example in the field of energy is presented and discussed, taking into account the experts experience in different fields and inaccurate concepts of information, efficiency and results of the proposed model.
Keywords :
Group Decision Making , Interval-Valued Fuzzy Sets , Possibilistic Statistical Concepts , Sustainable Energy Program Selection , System Reference Point
Journal title :
Journal of Quality Engineering and Production Optimization
Serial Year :
2019
Record number :
2514550
Link To Document :
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