首页|Multi-population particle swarm optimization algorithm for automatic design of steel frames

Multi-population particle swarm optimization algorithm for automatic design of steel frames

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Steel structures are widely used;however,their traditional design method is a trial-and-error procedure which is neither efficient nor cost effective.Therefore,a multi-population particle swarm optimization(MPPSO)algorithm is developed to optimize the weight of steel frames according to standard design codes.Modifications are made to improve the algorithm performances including the constraint-based strategy,piecewise mean learning strategy and multi-population cooperative strategy.The proposed method is tested against the representative frame taken from American standards and against other steel frames matching Chinese design codes.The related parameter influences on optimization results are discussed.For the representative frame,MPPSO can achieve greater efficiency through reduction of the number of analyses by more than 65％and can obtain frame with the weight for at least 2.4％lighter.A similar trend can also be observed in cases subjected to Chinese design codes.In addition,a migration interval of 1 and the number of populations as 5 are recommended to obtain better MPPSO results.The purpose of the study is to propose a method with high efficiency and robustness that is not confined to structural scales and design codes.It aims to provide a reference for automatic structural optimization design problems even with dimensional complexity.The proposed method can be easily generalized to the optimization problem of other structural systems.

steel framemulti-population particle swarm optimizationautomatic structural optimization design

Wenchen SHAN、Jiepeng LIU、Yao DING、Y.Frank CHEN、Junwen ZHOU

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Institute of Smart City and Intelligent Transportation,SouthwestJiaotong University,Chengdu 610000,China

School of Civil Engineering,Chongqing University,Chongqing 400045,China

Department of Civil Engineering,the Pennsylvania State University,Middletown,PA 17057,USA

国家自然科学基金国家自然科学基金Postdoctoral Fellowship Program of CPSFSpecial Support of Chongqing Postdoctoral Science Foundation国家重点研发计划

5230814252208185GZC202333342021XM20392022YFC3801700

2024

10.1007/s11709-024-1037-7

结构与土木工程前沿
高等教育出版社

结构与土木工程前沿

CSTPCDEI
影响因子：0.082
ISSN：2095-2430
年,卷(期)：2024.18(1)
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