An Approach to Rank Complex Alternatives Based on Behaviors

To overcome the drawbacks that individual preference information for uncertainties is rarely considered in current complex alternative ranking methods usually resulting in unreasonable alternative rankings, an approach to rank complex alternatives based on behaviors is presented by means of prospect theory. The presented approach introduces a new analysis structure to decompose a complex problem into some simple components and facilitate judgments, based on which, a ranking procedure is proposed. This proposed procedure, which can reflect characteristics of complex system such as nonlinear and emergence, is performed upwards for alternatives one by one, and introduces individual preferences for gains, losses and probabilities on each element in the analysis structure. Consequently, the presented approach is able to rank complex alternatives correctly and reasonably. A numerical case proves its applicability.