A fuzzy TOPSIS for assessing higher vocational education development levels in uncertainty environments

Issue title: Some highlights on fuzzy systems and data mining

Guest editors: Shilei Sun, Silviu Ionita, Eva Volná, Andrey Gavrilov and Feng Liu

Article type: Research Article

Authors: Li, Xuefeng^a | Chen, Kai^a | Ruan, Junhu^b | Shi, Chenghua^{c; *}

Affiliations: [a] School of Business Administration, Northeastern University, Shenyang, P.R. China | [b] Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong | [c] School of Management Engineering and Business, Hebei University of Engineering, Handan, China

Correspondence: [*] Corresponding author. School of Management Engineering and Business, Hebei University of Engineering, Handan, China. Tel.: +86 0310 8579372; Fax: +86 0310 6025698; E-mail: [email protected].

Abstract: It has an important practical significance to assess the higher vocational education development level in one specific region, but few effective methods are reported in the literature. Based on the practical challenges, we propose a fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) for assessing higher vocational education development levels. Firstly, in order to deal with decision-makers’ preferences on interval numbers, we develop a preference-based fuzzy number comparison method and then integrate it with the classic TOPSIS method to formulate a fuzzy TOPSIS method. An application example shows the effectiveness of the work and observes the impact of decision-makers’ preferences on the assessment results. Several insights are also found to improve the assessment process in the real world.

Keywords: Fuzzy number comparison, α-cut, fuzzy TOPSIS, higher vocational education, development level assessment, optimism degrees

DOI: 10.3233/JIFS-169194

Journal: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 6, pp. 3083-3093, 2016