Multi objective optimization of static behavior of FGM multi layered plate based on exact solution and using neural-genetic method

In this paper، a new formulation for exact bending analysis of FGM multi-layered plate with power-law distribution of properties in the each layer based on three-dimensional inhomogeneous elasticity is presented. Multi objective optimization is implemented for the plate under sinusoidal and uniform transverse load. Variables are the thickness of each layer and exponential or power law inhomogeneous parameters in the each layer. Objectives of optimization are taken to be mass and maximum transverse deflection of the plate. Constraint of optimization is the local safety factor based on stress criteria، that must always be larger than 1. Objective functions are coded in MATLAB software. The plate has 6 layers with power-law distribution of properties at faces and exponential properties at layers of the core. Objective functions is simulated with neural network because of the computational cost involved. Also، in this thesis، non-dominated sorting genetic algorithm method is used for multi objective optimization. Results show that the use of faces with high stiffness an core with low stiffness instead of homogeneous plate reduces the mass and the maximum normal deformation significantly.