Constructive Solid Geometry Based Topology Optimization Using Evolutionary Algorithm

Over the past two decades, structural optimization has been performed extensively by researchers across the world. Most recent investigations have focused on increasing the efficiency and robustness of gradient based optimization techniques and extending them to multidisciplinary objective functions. The existing global optimization techniques suffer with requirement of enormous computational effort due to large number of variables used in grid discretization of problem domain. The paper proposes a novel methodology named as Constructive Geometry Topology Optimization Method (CG-TOM) for topology optimization problems. It utilizes a set of nodes and overlapping primitives to obtain the geometry. A novel graph based repair operator is used to ensure consistent design and real parameter genetic algorithm is used for optimization. Results for standard benchmark problems for compliance minimization have been found to give better results than existing methods in literature. The method is generic and can be extended to any two or three dimensional topology optimization problem using different primitives.