Probabilistic-based expressions in behavioral multi-attribute decision making considering pre-evaluation

Abstract

A behavioral multi-attribute decision making (BMADM) problem with probabilistic-based expressions is studied by considering decision-maker’s (DM) risk attitude and pre-evaluation. With consideration of information expressions for uncertainty, probabilistic interval numbers (PINs) and probabilistic linguistic terms (PLTs) are utilized to depict pre-evaluation information with respect to quantitative and qualitative attributes, respectively. Then surrounding the two kinds of probabilistic-based expressions, we propose a BMADM method with DM’s risk attitude being included based on regret theory. First, through taking into account characteristics of risk, we develop a basic utility function and a regret–rejoice function by considering risk-averse, risk-neutral and risk-seeking preference coefficients. Second, risk-based utility functions are examined for measuring PINs and PLTs. The third element is the establishment of optimization models for handling probability incompleteness to fully utilize the information. In the fourth step, a weighted comprehensive risk-based utility measurement is presented as a basis for making a selection. The final phase of the research is the application of the proposed method to one case, along with sensitivity and comparative analyses, as a means of illustrating the applicability and feasibility of the new method.