Three fuzzy models are employed to combine with an improved imposed-on penalty approach for attacking a nonlinear multiobjective in the mixed-discrete optimization problem. The model can generate a unique compromise solution with the maximum design satisfaction. A systematic study of the proposed penalty method is presented, including the forms of penalty function and the values of each parameter. A default value of the parameter and an optimization algorithm are presented in the paper. One can easily program and reach the solution by any nonlinear programming method. Several structural design systems serve as the illustrative examples. The presented strategy is suggested as appropriate for solving a generalized mixed-discrete optimization problem.
