The standard Goal Programming (GP) model considers the aspiration levels (goals) as precise and deterministic. However, in practice, there are many decision-making situations where the decision-maker is not able to establish the goal values precisely. The goals fuzziness is more related to the nature of the objectives involved in the decisionmaking situation. The Fuzzy Goal Programming (FGP) Model has been developed in the earliest of the 80s to deal with such situations. The concept of membership functions, based on fuzzy sets theory, has been used for modelling the goals fuzziness in the GP. The aim of this paper is to give an overview of the current state-of-the art regarding the FGP model.

Several classifications of the Multiple Objectives Programming (MOP) models have been proposed in the literature. In general, these classifications are based on the timing of introducing the decision-maker's (DM) preferences and the type of the required information about the parameters of the decision-making situation. The DM's preference information can take different forms such as: weights, priority levels, thresholds or trade-offs among the objectives. The Goal Programming (GP) is one of the well-known MOP models. The different GP formulations deal differently with the DM's preferences. The aim of this paper is to propose a new typology of the GP variants based on the way that the DM's preferences are considered.

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