MULTI-OBJECTIVE OPTIMIZATION OF LAMINATED COMPOSITE PLATE USING A NON-DOMINATED SORTING GENETIC ALGORITHM

Laminated composite constructions of panels and other structural elements are currently being used for many applications in aerospace, automotive, civil and defence industries. Laminated composites have general advantages over more traditional materials such as greater specific strength, specific stiffness, corrosion and fatigue resistance among others. Optimization of composite laminates with respect to ply angels to maximize the strength is necessary to realize the full potential of fiber reinforced materials. In this paper a modified Non-Dominated sorting Genetic Algorithm is used to obtain pareto-optimal design of composite laminate square plate. The objectives are to minimize the weight and deflection of graphite/epoxy square plate subjected to the constraint that the Tsai-Wu failure factor ( zeta ) should be less than or equal to one. The multi-objective optimization algorithm used in this paper has better sorting, incorporates elitism and no sharing parameter needs to be chosen a priori.