Lay-up sequence design of laminate composite plates and a cylindrical skirt using ant colony optimization

Abstract

For laminated composite materials, the stacking sequence design is indispensable to make efficient use of the material properties. Laminated composites are usually fabricated from unidirectional plies of given thickness with fibre orientations limited to a small set of angles (e.g. 0°, +45°, −45°, and 90°). This leads to a combinatorial optimization problem, which is rather complex to solve. In this article, an adaptation of a popular swarm intelligence-based combinatorial optimization technique called ant colony optimization (ACO) for lay-up sequence optimization of laminate composite structures is explored. The basic ACO algorithm is hybridized with a neighbourhood search algorithm built with tabu search features to improve the overall performance of the algorithm. Numerical experiments have been carried out by first considering the popularly used bench mark problem of buckling and failure load optimization of a laminate composite plate. Later, the ACO is employed to solve a multi-objective problem of simultaneous optimization of cost and weight of a hybrid laminate composite cylindrical skirt. Numerical studies carried out in this article clearly indicate that the ACO combined with an appropriate neighbourhood search can be an effective combinatorial optimization tool for stacking sequence optimization of laminate composite structures and the computational performance is found to be superior when compared to other popular meta-heuristic algorithms.