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Automotive body frame structures play crucial roles in the achievement of dynamic and crashworthiness performance, and their cross-sections must fulfill various required characteristics. However, cross-sectional shape design is complex and relies on designers' intuitions, since automotive body frames are fabricated from many sheet metal parts having complex interdependencies, a problematic situation for optimization via software. This paper proposes a cross-sectional shape generation method satisfying a range of required cross-sectional properties for early design stages. Shape generation problems are formulated as multiobjectsve optimization problems, solved using genetic algorithms and a variety of cross-sections can be obtained as Pareto optimal solution sets.