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This paper presents an efficient bi-level optimization technique to obtain the optimal stacking sequence for symmetric composite structures. The proposed approach involves two levels of modeling and optimization. The first level of the optimization procedure is used to minimize the weight of the composite structure. At this level, lamination parameters and the number of plies of specified angles (0, ±45 and 90 degree) are design variables, buckling load factor is treated as a constraint, and the weight of the structure is to be minimized using continuous-discrete particle swarm optimization algorithm. Next, at the second level the location of each ply orientation through the thickness (i.e. the layup of the panel) is found. At the second level, optimum stacking sequence is sought to maximize the load bearing capacity of the structure with respect to the buckling. The proposed methodology is applied to two test cases. Results show that the approach improves the buckling load factor of the structure without any weight penalty. [ABSTRACT FROM AUTHOR]

This paper presents computationally an efficient multi-objective reliability-based design optimization (RBDO) method for composite structures with uncertain design parameters. The approach adopted is based on a novel hybrid decomposing-based multi-objective particle swarm optimization and sequential quadratic programming algorithms, which is coupled with bi-level modelling and optimization strategy of composite structures and RBDO using Cross entropy method. The reliability analysis considers the rare-event corresponding to the limit states, which is based on Tsai-Wu failure index. In addition, the growing requirements for composite structural design with a minimum weight, introduces significant research challenges in the RBDO approach as the weight and reliability are the two important opposing design requirements. To address this research challenges, the proposed approach involves both reliability and weight as objective functions. A laminated composite plate and benchmark problems were used to demonstrate the efficiency and accuracy of the proposed method. Results show that the proposed method provides computationally efficient and accurate evaluations of the performance of the design of composite structures in comparison to the conventional Monte Carlo simulation method and can provide a potential for solving large-scale multi-objective RBDO of composite structures design problems. [ABSTRACT FROM AUTHOR]