The traditional frameworks for fuzzy linear optimization problems are inspired by the max-min model proposed by Zimmermann using the Bellman-Zadeh extension principle. This paper attempts to view fuzzy multiobjective linear programming problem (FMOLPP) from a perspective of preference modeling. The fuzzy constraints are viewed as negative preferences for rejecting what is unacceptable while the objective functions are viewed as positive preferences for depicting satisfaction to what is desired. This bipolar view enable us to handle fuzzy constraints and objectives separately and help to combine them in distinct ways. The optimal solution of FMOLPP is the one which maximizes the disjunctive combination of the weighted positive preferences provided it satisfy the negative preferences combined in conjunctive way. © 2012 Springer-Verlag.