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논문 기본 정보

자료유형
학술저널
저자정보
Kaveh, A. (Centre of Excellence for Fundamental Studies in Structural Engineering, Iran University of Science and Technology) Fahimi-Farzam, M. (Centre of Excellence for Fundamental Studies in Structural Engineering, Iran University of Science and Technology) Kalateh-Ahani, M. (Centre of Excellence for Fundamental Studies in Structural Engineering, Iran University of Science and Technology)
저널정보
테크노프레스 Structural engineering and mechanics : An international journal Structural engineering and mechanics : An international journal 제44권 제3호
발행연도
2012.1
수록면
379 - 403 (25page)

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In recent years, the need for optimal design of structures under time-history loading aroused great attention in researchers. The main problem in this field is the extremely high computational demand of time-history analyses, which may convert the solution algorithm to an illogical one. In this paper, a new framework is developed to solve the size optimization problem of steel truss structures subjected to ground motions. In order to solve this problem, the covariance matrix adaptation evolution strategy algorithm is employed for the optimization procedure, while a generalized regression neural network is utilized as a meta-model for fitness approximation. Moreover, the computational cost of time-history analysis is decreased through a wavelet analysis. Capability and efficiency of the proposed framework is investigated via two design examples, comprising of a tower truss and a footbridge truss.

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