A structural reanalysis assisted harmony search for the optimal design of structures

Structural optimization usually requires a large amount of time-consuming structural analyses to evaluate the feasibility of the designs, which obstructs its application in large-scale problems. This study proposed a structural reanalysis-assisted harmony search (RAHS) algorithm for structural optimization. The RAHS utilizes the combined approximation (CA) technique instead of direct finite element analysis to evaluate the performances of the modified structures generated in iterations. Different from existing approaches, the proposed RAHS will update the reanalysis design point set and select the best reanalysis design point based on the similarity of the design vectors to improve the accuracy of the CA in a large search space. The RAHS also develops a diversity-based error criterion to accommodate the accuracy requirements of CA in different search phases of the harmony search. Five benchmark examples are utilized to examine the performances of the proposed RAHS. The results demonstrate that the Cosine distance outperforms the other four design point selection approaches, and the diversity-based error criterion can significantly reduce the computational cost. Compared with the penalty-based method and the improved Deb rule, the number of FE-based structural analyses can be lessened by about 90% and 50%, respectively, while yielding similar optimal designs. (c) 2022 Elsevier Ltd. All rights reserved.

Automated summary

This study proposes a structural reanalysis-assisted harmony search algorithm for structural optimization. It utilizes combined approximation technique to evaluate modified structures and develops a diversity-based error criterion to accommodate accuracy requirements. Experimental results demonstrate the algorithm's high accuracy and low computational cost in large-scale problems.