A New Assessment Method of new Energy in Regional Sustainable Development based on Hesitant Fuzzy Information

Hongdi Yao; Wenxing Li

Journal Name:

Journal of Industrial Engineering and Management

Publication Year:

2014

DOI:

http://dx.doi.org/10.3926/jiem.1299

Key Words:

Author Name	University of Author
Hongdi Yao	Beijing University of Technology
Wenxing Li	Beijing University of Technology

Abstract (2. Language):

Purpose: The new energy has been an important driving force in region sustainable development. It is a critical issue to evaluate the role of new energy in region sustainable development. Design/methodology/approach: To deal with this issue, this paper proposes a new score function, in which, both mean and variance are considered. Then it introduces the basic operators, such as hesitant fuzzy weighted averaging operator and hesitant fuzzy weighted geometric operator to get the comprehensive assessment provided by the decision maker on each attribute. Findings: Due to the drawbacks of existing methods with hesitant fuzzy information, this paper puts forward a method and the procedure to solve the MADM (multiple attribute decision making) problem. And an illustrative example is demonstrated to verify the reliability of the proposed method. Research limitations/implications: The method can be used to evaluate the new energy in regional sustainable development, but it cannot solve the problems with many experts. Practical implications: Based on the new framework, a case study is carried out to verify its applicability and validity. The research can fill the gaps for the assessment framework of new energy in regional sustainable development. This paper is of practical value in real life, which is the application of some techniques. Originality/value: This paper describes in detail in evaluating the role of new energy in region sustainable development. And a new score function is proposed with hesitant fuzzy information, that is, the idea of variance is introduced to form a new score function to measure the deviation of hesitant fuzzy elements. Meanwhile, the basic operator, such as hesitant fuzzy weighted averaging operator and hesitant fuzzy weighted geometric operator are introduced to integrate the hesitant fuzzy information.

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REFERENCES

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