Interactive Multiobjective Optimization Using a Set of Additive Value Functions

Abstract. In this chapter, we present a new interactive procedure for multiobjective optimization, which is based on the use of a set of value functions as a preference model built by an ordinal regression method. The procedure is composed of two alternating stages. In the first stage, a representative sample of solutions from the Pareto optimal set (or from its approximation) is generated. In the second stage, the Decision Maker (DM) is asked to make pairwise comparisons of some solutions from the generated sample. Besides pairwise comparisons, the DM may compare selected pairs from the viewpoint of the intensity of preference, both comprehensively and with respect to a single criterion. This preference information is used to build a preference model composed of all general additive value functions compatible with the obtained information. The set of compatible value functions is then applied on the whole Pareto optimal set, which results in possible and necessary rankings of Pareto o...

• Type: Conference
• Year: 2008
• Where: DAGSTUHL
• Authors: José Rui Figueira, Salvatore Greco, Vincent Mousseau, Roman Slowinski
• Keywords: DAGSTUHL 2008, Ordinal Regression Methods, Pareto Optimal Set, Software Engineering, Value Functions