Concurrent Genetic Algorithms for Optimization of Large Structures

Authors:
Publisher website
Google Scholar
Abstract
In a recent article, the writers presented an augmented Lagrangian genetic algorithm for optimization of structures. The optimization of large structures such as high‐rise building structures and space stations with several hundred members by the hybrid genetic algorithm requires the creation of thousands of strings in the population and the corresponding large number of structural analyses. In this paper, the writers extend their previous work by presenting two concurrent augmented Lagrangian genetic algorithms for optimization of large structures utilizing the multiprocessing capabilities of high‐performance computers such as the Cray Y‐MP 8/864 supercomputer. Efficiency of the algorithms has been investigated by applying them to four space structures including two high‐rise building structures. It is observed that the performance of both algorithms improves with the size of the structure, making them particularly suitable for optimization of large structures. A maximum parallel processing speed of 7.7 is achieved for a 35‐story tower (with 1,262 elements and 936 degrees of freedom), using eight processors.

This publication has 4 references indexed in Scilit: