A Robust Group Multiple Attributes Decision-Making Method Based on Risk Preference of the Decision Makers

A Robust Group Multiple Attributes Decision-Making Method Based on Risk Preference of the Decision Makers

In this paper, we propose a robust multiple attributes decision-making (MADM) method based on prospect theory to reflect the decision behavior of a decision maker in face of risk. Instead of identifying the reference points, the decision makers only need to determine the feasible ranges for each attribute by their knowledge and experience in the beginning of the decision process. The psychological value distances are defined to measure the overall prospect values of each alternative reference to extreme feasible solutions using the value function and the additive weighting method. This study further extends the method to a group decision environment. The preferences of more than one decision maker are internally aggregated into the decision procedure. Performance of the proposed algorithms is comparatively analyzed and sensitivity analysis is conducted. The results show that it is an appropriate and robust MADM method.