Multiattribute additive value functions constitute an important class of models for multicriteria decision making. Such models are often used to rank a set of alternatives or to classify them into pre-defined groups. Preference disaggregation techniques have been used to construct additive value models using linear programming techniques based on the assumption of monotonic preferences. This paper presents a methodology to construct non-monotonic value function models, using an evolutionary optimization approach. The methodology is implemented for the construction of multicriteria models that can be used to classify the alternatives in pre-defined groups, with an application to credit rating.
- Calculus of Variations and Optimal Control; Optimization
- Operations Research/Decision Theory
- Business/Management Science, general
- Multicriteria decision making
- Value functions
- Evolutionary optimization
In multicriteria decision making (MCDM), a wide range of criteria aggregation forms are used for preference modeling and decision making purposes. These include functional forms originating from the multiatribute value theory (Keeny and Raiffa 1993), relational forms based on the outranking relations theory (Roy 1991), and symbolic forms which have been recently proposed within the context of the dominance- based rough sets approach (Greco et al. 2001).