This paper discusses an optimized structural plate of plywood composite that consists of top and bottom plywood flanges and a core of plywood ribs. The objective function is structure’s weight. Typical constrains are used - maximal stress criteria and maximal deformation criteria - are used. The optimization is done by Genetic Algorithm and optimization results are used to train Feed- Forward Artificial Neural Network. The numerical simulation of plywood structure is done by using classical-linear Kirchoff-Love theory of multilayer plate and Finite Element Method. As a result there is proposed an effective optimization methodology for plywood composite material. The most rational (according to strength-stiffness criteria) plywood composite macro-structure are obtained for some typical cases.