The increasing complexity of applications encountered in multiobjective optimization leads us today to apply decision models to combinatorial sets of solutions which are implicitly defined. This significantly complicates the decision process and, in particular, the construction of a preference model fitting the objectives of the decision maker as well as the calculation of the optimal decision. Instead of approaching independently and separately these two subjects, we introduce incremental decision procedures aiming to integrate and combine the elicitation of preferences and the calculation of the preferred solution in order to determine the optimal choice without fully specifying the decision model. In these new interactive resolution schemes, asking preference questions to the decision maker during the exploration of the set of solutions allows to focus the elicitation of preferences on information that is really useful for separating competing solutions and thus reducing the number of questions required. This is the main benefit of the incremental approach to multiobjective decision making. 

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