Developing sorting models using preference disaggregation analysis: An experimental investigation

Within the field of multicriteria decision aid, sorting refers to the assignment of a set of alternatives into predefined homogeneous groups defined in an ordinal way. The real-world applications of this type of problem extend to a wide range of decision-making fields. Preference disaggregation analysis provides the framework for developing sorting models through the analysis of the global judgment of the decision-maker using mathematical programming techniques. However, the automatic elicitation of preferential information through the preference disaggregation analysis raises several issues regarding the impact of the parameters involved in the model development process on the performance and the stability of the developed models. The objective of this paper is to shed light on this issue. For this purpose the UTADIS preference disaggregation sorting method (UTilités Additives DIScriminantes) is considered. The conducted analysis is based on an extensive Monte Carlo simulation and useful findings are obtained on the aforementioned issues.