TODIM-VIKOR method for performance evaluation of school-enterprise cooperation in vocational colleges under 2-tuple linguistic Pythagorean fuzzy sets

Author:

Han Yongguang1,Xu Xinrui2

Affiliation:

1. Intelligent Construction Technology Application Service Center of Chongqing City Vocational College, Chongqing, China

2. School of Civil Engineering, Chongqing University of Arts and Sciences, Chongqing, China

Abstract

As an important way to cultivate talents, school-enterprise cooperation is highly praised by the educational and economic circles of all countries. Vocational education spans enterprises and schools, and is an education of cross-border innovation. Vocational schools should make the people they cultivate meet the needs of the market and enterprises, and carry out in-depth school-enterprise cooperation is one of the effective ways. The school-enterprise cooperation between vocational colleges and enterprises makes vocational education more targeted and practical, and plays an important role in the training of skilled talents. It is not only an inevitable requirement for enterprise development and participation in competition, but also an important direction of China’s vocational education reform, and is the fundamental outlet for the development of China’s vocational education. The performance evaluation of school-enterprise cooperation in vocational colleges is classical multiple-attribute group decision-making (MAGDM) issues. Recently, the TODIM and VIKOR method has been used to solve MAGDM issues. The 2-tuple linguistic Pythagorean fuzzy sets (2TLPFSs) are used as a tool for characterizing uncertain information during the performance evaluation of school-enterprise cooperation in vocational colleges. In this manuscript, we design the 2-tuple linguistic Pythagorean fuzzy TODIM-VIKOR(2TLPF-TODIM-VIKOR) method to solve the MAGDM under 2TLPFSs. In the end, a numerical case study for performance evaluation of school-enterprise cooperation in vocational colleges is given to validate the proposed method.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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