A novel weighted graph representation-based method for structural topology optimization. (March 2021) - Jie, Xing; Ping, Xu; Shuguang, Yao; Hui, Zhao; Ziliang, Zhao; Zhangjun, Wang
Highlights: A weighted graph representation for structural topology optimization is proposed. A dual self-adaptive differential evolution (DE) process is developed. The proposed method can effectively deal with topology optimization problems. Abstract: This paper proposes a novel weighted graph representation for structural topology optimization. Based on the graph theory, a weighted adjacency matrix is first introduced to collect the connectivity information and the corresponding width value of the edges. Accordingly, each edge with different width is symbolized as a rectangle to represent the mapped topology for a regular meshed design domain. To reduce the computational cost, an improved differential evolution (DE) process with a dual self-adaptive mutation operator which is named as the DSADE is proposed to utilize as an optimizer. Finally, three classical numerical tests are carried out. The results indicate that the present method can effectively deal with a series of structural topology optimization problem with different boundary constraints. In addition, by comparing with the related methods in literatures, it is found that the present method can achieve an optimized solution without complex initial definitions.