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A hybrid search optimization is presented in order to optimize hybrid laminated fibrous composite E-springs for vehicle suspension systems. This optimization is conducted with both of the geometrical configuration and laminate structure of the E-spring. A genetic algorithm along with a hill-climbing random-walk approach are used through a developed NURBS-based technique in order to conduct this optimization. A mathematical-modeling-based mid-ware technology is introduced in order to fully automate the optimization process through linking the run engines of mathematical modeling and finite element analysis from within the mathematical modeling engine. A hybrid approach of the inter-laminar shear stress and Tsai-Wu criteria is first implemented in order to identify failure indices of the resulting optimum shape and laminate structure.