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

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Abstract

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.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Nos. 52308142 and 52208185), Postdoctoral Fellowship Program of CPSF (No. GZC20233334), Special Support of Chongqing Postdoctoral Science Foundation (No. 2021XM2039) and National Key Research and Development Program of China (No. 2022YFC3801700).

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Authors and Affiliations

  1. Institute of Smart City and Intelligent Transportation, Southwest Jiaotong University, Chengdu, 610000, China

    Wenchen Shan

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

    Jiepeng Liu, Yao Ding & Junwen Zhou

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

    Y. Frank Chen

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  1. Wenchen Shan
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  2. Jiepeng Liu
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  3. Yao Ding
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  4. Y. Frank Chen
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  5. Junwen Zhou
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Correspondence to Junwen Zhou.

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Shan, W., Liu, J., Ding, Y. et al. Multi-population particle swarm optimization algorithm for automatic design of steel frames. Front. Struct. Civ. Eng. 18, 89–103 (2024). https://doi.org/10.1007/s11709-024-1037-7

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