Optimization of multispan ribbed plywood plate macrostructure for multiple load cases
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 – maximal stress criteria and maximal deformation criteria – are used. The optimization is done by Genetic Algorithm (GA), 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, an effective optimization methodology for plywood composite material is proposed. The most rational (according to strength-stiffness criteria) plywood composite macrostructure is obtained for some typical cases.