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Simultaneous topology, shape, and size optimization of trusses, taking account of uncertainties using multi-objective evolutionary algorithms

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Abstract

This paper proposes the design of trusses using simultaneous topology, shape, and size design variables and reliability optimization. Objective functions consist of structural mass and reliability, while the probability of failure is set as a design constraint. Design variables are treated to simultaneously determine structural topology, shape, and sizes. Six test problems are posed and solved by a number of multi-objective evolutionary algorithms, and it is found that Hybridized Real-Code Population-Based Incremental Learning and Differential Evolution is the best performer. This work is considered an initial study for the combination of reliability optimization and simultaneous topology, shape, and sizing optimization of trusses.

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Acknowledgements

This work was supported by the Graduate Engineering Camp Fund, Faculty of Engineering, Khon Kaen University, Thailand, and the Thailand Research Fund (TRF).

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  1. Sustainable and Infrastructure Research and Development Center, Department of Mechanical Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen, 40002, Thailand

    Teerapol Techasen, Kittinan Wansasueb, Natee Panagant, Nantiwat Pholdee & Sujin Bureerat

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  1. Teerapol Techasen
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Correspondence to Sujin Bureerat.

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Techasen, T., Wansasueb, K., Panagant, N. et al. Simultaneous topology, shape, and size optimization of trusses, taking account of uncertainties using multi-objective evolutionary algorithms. Engineering with Computers 35, 721–740 (2019). https://doi.org/10.1007/s00366-018-0629-z

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