Decision-maker's preferences modeling in the stochastic goal programming

Generally we assume that the decision-maker is able to delimit with precision and without difficulty, the values of the goals associated with the objectives of a decision-making situation. However, such values may be probabilistic in nature. In such situation, the decision-maker does not know with certainty the values of the goals related to the different objectives. To deal within such decision-making situations, the literature proposes several techniques, based on the stochastic goal programming (SGP) model. These approaches do not take into account explicitly the decision-maker's preferences. In the present paper, we exploit the concept of the satisfaction functions to explicitly integrate the decision-maker's preferences in the SGP model.