Set-based Search and Selection of Concepts

The common search for a Pareto-optimal set, and the associated front, usually serves as a preprocessing stage for a Multi-Criteria Decision Making (MCDM). In that case the optimization provides information to support the selection of a final solution from a feasible space of solutions. Here, we are interested in a rather different MCDM problem and its associated preprocessing stage. Our study concerns a Pareto-based preprocessing stage for the selection of a concept, or a sub-set of concepts, out of a finite set of feasible concepts. The methodology used here is termed the Set Based Concept (SBC) approach (e.g., [1]). In the SBC approach, each concept is understood as a set of feasible solutions with some common aspects. This reflects the fact that a concept is not a final solution. Figure 1 illustrates the main idea of the SBC approach. In figure 1 there are 3 concepts of aircrafts, which are marked by three colors (from left to right as the red, blue, and white concepts). The colored performance vectors are typical performances of solutions belonging to the associated-color concept.