Abstract: Attractive issues related with membership functions in fuzzy nonlinear programming have been discussed in depth in this study. Initially, an approach to constructing unilateral and bilateral membership functions is introduced to deal with soft constraints. In order to facilitate solution of fuzzy nonlinear programming problems, a procedure towards linearization of membership functions is presented, along with a novel modeling methodology to formulate fuzzy nonlinear programming with piecewise linear membership functions. Therein, taking advantage of compatible configuration of binary variables, relations between the sub-membership-functions are explicitly characterized, which could efficiently help prevent constraint-free problems and achieve satisfied solutions. Finally, a numerical example is employed to demonstrate the benefits of the contribution.