Two-Level Weight Optimization of Composite Laminates Using Integer Programming

Optimization of composite laminates requires the satisfaction constraints where design ply thicknesses and orientations can only take discrete values prescribed by manufacturers. Heuristics such as particle swarm or genetic algorithms are inefficient in cases because they provide suboptimal solutions when number variables is large. They also computationally expensive handling combinatorial nature problem. In contrast, with help binary decision variables, mixed integer programming be adopted to optimize efficiently. This paper presents an approach reformulate lamination parameters failure functions variables. The buckling load maximization for a simply supported laminated plate initially demonstrated using linear programming. Next, laminate weight minimized varying plies given external bi-axial compressive subjected material constraints. A variation minimization fixing assuming changes thicknesses. achieved sequential two-level optimization having uniform thickness. Finally, scalability study performed evaluate performance different problem sizes. It that all three formulations achieve significant gain robustness over standard heuristic solvers.