Affiliations: [a] Business School, Hohai University, Nanjing, China
| [b] Business School, University of Shanghai for Science and Technology, Shanghai, China
| [c] Business School, Sichuan University, Chengdu, China
| [d] China Railway Construction Bridge Engineering Bureau Group CO., LTD, Yinchuan, China
| [e] School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, China
Correspondence:
[*]
Corresponding author. Shaojian Qu, Business School, University of Shanghai for Science and Technology, Shanghai,
China. Tel.: 15601980161; E-mail: [email protected].
Abstract: In multiattribute decision making problem, it is usually that the opinions of agent may be influenced by close friends or people with similar interests among his social network. This situation could act on the evaluation process of agent toward candidates, thereby affecting the overall two-sided matching results. This paper proposes a framework based on social network analysis. It can effectively achieve multiattribute social network matching that the relative weights of influencers are unknown before. In the proposed framework, the complete trust assessment matrix can be obtained through depicting the trust propagation relationship between agent and influencers. According to the trust assessment result, a nonlinear optimization model is developed to calculate the unknown weights of influencers, and then the obtained weights of influencers are integrated into the two-sided evaluation process. Furthermore, two multi-objective optimization models are constructed to manage the rational agents and conservative agents. Based on the multi-objective optimization models, we generate the optimal matching pairs. Finally, detailed comparison analysis and discussion are presented to check the effectiveness of the proposed social network matching method.
