A new approach to multiobjective optimization is proposed. When two or more objectives must be simultaneously be optimized, the most important objective function is adopted as the primary criterion and the other objective functions are transformed into constraints by imposing some lower and upper bounds on them. Then the single objective optimization is solved by the feasible direction method. The conventional ε-constraint method uses the previous optimization results as initial design points because these design points are in the feasible region. So successive optimization is necessary to obtain several Pareto optimal points. But the proposed method generate independent feasible points in order to use as initial points in numerical optimization. This technique makes it possible to adopt parallel processing in multiobjective optimization. Multiobjective optimization combined with parallel processing is very efficient solution technique in that there is no time increase with increased Pareto optimal points. Numerical example is presented for multiobjective optimization of steel box girder bridge design.
