Hybrid Multiple Attribute Two-Sided Matching Decision Making Based on Grey Relational Fractional Programming Method

Sung-Chol Jang, Gol Kim

Abstract: In this paper, for a multiple attributes two-sided decision making problems, takes into account different formats of evaluation information of matching objects and proposes a method for dealing with such two-sided matching decision making problems. A methodology for determining the comprehensive weights of attributes of matching objects under the hybrid attribute environment based on some method for determining the subject and objective attribute weights is presented. Based on the grey relational degree and the technique for order preference by similarity to ideal solution (TOPSIS) principle, optimal degrees of membership for matching objects by fractional programming is proposed and is defined matching satisfactory degree by it, and gets the best matching for the matching objects by solving a binary integer programming problem. The illustrative examples show the feasibility and effectiveness of the proposed method

Keywords: decision making, two-sided matching, optimization model, grey relational analysis, fractional programming method