Affiliation:
1. College of Information Science and Engineering, Hunan Normal University, China
Abstract
This chapter proposes group-oriented multi-attribute decision-making based on mixed advantage-disadvantage degree (GOMADMMADD) method to deal with group-oriented decision analysis. Based on the strict attribute relationship between group members, this method proposes the concepts of “local advantage-disadvantage degrees” and “advantage-disadvantage degrees,” which solves the challenge of group-oriented multi-attribute decision-making (GOMADM). However, this method still has the problem that the number of groups to be evaluated increases exponentially. Therefore, the authors first improved the GOMADMMADD method and proposed decision-making method based on dominance-based rough sets (GMADMDRS). Then, the “advantage” neighborhood operators and “disadvantage” neighborhood operators of groups are introduced to define the “advantage-disadvantage neighborhood degree” (ADND), and the GMADMDRS method is optimized by using ADND. The experimental results show that both GOMADMMADD method and GMADMDRS method effectively evaluate the population, and the optimized GMADMDRS algorithm is consistent in the experimental results, and the time performance has been greatly improved, and the computational performance has been significantly improved, which has practical significance to solve the problem of exponential growth of the number of groups to be evaluated. These methods provide a novel perspective and effective method for group oriented multi-attribute decision-making.