Multi-Criteria Decision Making Analysis Based on Target-Oriented OWA Operator

Abstract

The target-oriented multi-criteria decision making is investigated based on the ordered weighted averaging (OWA) operator. The criteria evaluations are measured by using the likelihood of satisfying the targets of criteria. To aggregate the target-oriented criteria evaluations, the target-oriented OWA operator is firstly introduced, in which the target-oriented criteria evaluations are reordered and then aggregated by using the weight vector associated with the position of criteria evaluations. Four types of targets about criteria evaluations and four types of attitudinal characters about criteria weight vector are introduced, based on which, models are given to identify the potential best alternative(s), and estimate the ranges of attitudinal characters about criteria weight vector for each potential best alternative. The proposed models can not only analyze the sensitivity of each potential best alternative, but also can explore the impact of targets about criteria evaluations and attitudinal characters about criteria weight vector on the decision results. Models are further established to find the best and worst ranking orders of each alternative based on targets about criteria evaluations, and give decision analysis by considering specific ranking orders of alternatives. The proposed method considers the targets about criteria evaluations and attitudinal character about criteria weight vector at the same time and can provide decision makers more choices. Several examples are given to illustrate the proposed methods.