Evolutionary algorithm and its application in structural topology optimization

This paper proposes a bio-inspired evolutionary computational algorithm for structure topology optimization. It integrates the merits of evolutionary structure optimization and level set method for structure topology optimization. Traditional Level Set Method algorithm depends on the initial topology to some extent. New holes cannot be evolved within the updated topology during the optimization iteration. The algorithm proposed in this paper combines the merits of ESO techniques with that of LSM scheme, allowing new holes to be automatically inserted in regions with low deformation energy at prescribed iterations of the optimization. The nodal neighboring region is adopted in the proposed algorithm. Numerical example shows that good result can be gotten through less optimization iteration. The approach can solve complex structures easily, in which holes cannot be properly layed out in advance. The proposed method considerably improves the ability of LSM to find the optimal topology. The validity and efficiency of the proposed algorithm are supported by some benchmark examples in this paper.