Models for evaluating the regional carbon emissions performance under the background of urban industrial agglomerations with hesitant fuzzy linguistic information

Article type: Research Article

Authors: Yang, Min^{a; b}

Affiliations: [a] School of Economics and Management, Wuhan University, Wuhan 430072, Hubei, China | [b] Yulin Normal University, Yulin 537000, Guangxi, China | Tel./Fax: +86 015177511792; E-mail: [email protected]

Abstract: In this paper, we investigate the multiple attribute decision making (MADM) problem based on the induced OWA (IOWA) operator with hesitant fuzzy linguistic information. Then, motivated by the ideal of induced OWA (IOWA) operator and Einstein operations, we have developed the induced hesitant fuzzy linguistic Einstein ordered weighted average (IHFLEOWA) operator. Then, we have utilized induced hesitant fuzzy linguistic Einstein ordered weighted average (IHFLEOWA) operator to develop an approach to solve the multiple attribute decision making problems for evaluating the regional carbon emissions performance under the background of urban industrial agglomerations. Finally, a practical example for evaluating the regional carbon emissions performance under the background of urban industrial agglomerations is given to verify the developed approach and to demonstrate its practicality and effectiveness.

Keywords: Multiple attribute decision making (MADM), hesitant fuzzy linguistic sets, induced hesitant fuzzy linguistic einstein ordered weighted average (IHFLEOWA) operator, regional carbon emissions performance, urban industrial agglomerations

DOI: 10.3233/KES-170367

Journal: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 21, no. 4, pp. 235-242, 2017