Abstract
SUMMARY Optimal design of tall buildings, as large-scale structures, is a rather difficult task. To efficiently achieve this task, the computational performance of the employed standard meta-heuristic algorithms needs to be improved. One of the most popular meta-heuristics is particle swarm optimization (PSO) algorithm. The main aim of the present study is to propose a modified PSO (MPSO) algorithm for optimization of tall steel buildings. In order to achieve this purpose, PSO is sequentially utilized in a multi-stage scheme where in each stage an initial swarm is generated on the basis of the information derived from the results of previous stages. Two large-scale examples are presented to investigate the efficiency of the proposed MPSO. The numerical results demonstrate the computational advantages of the MPSO algorithm. Copyright © 2012 John Wiley & Sons, Ltd.
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