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A new hybrid method for size and topology optimization of truss structures using modified ALGA and QPGA

    Nima Noii Affiliation
    ; Iman Aghayan Affiliation
    ; Iman Hajirasouliha Affiliation
    ; Mehmet Metin Kunt Affiliation

Abstract

Modified Augmented Lagrangian Genetic Algorithm (ALGA) and Quadratic Penalty Function Genetic Algo­rithm (QPGA) optimization methods are proposed to obtain truss structures with minimum structural weight using both continuous and discrete design variables. To achieve robust solutions, Compressed Sparse Row (CSR) with reordering of Cholesky factorization and Moore Penrose Pseudoinverse are used in case of non-singular and singular stiffness matrix, respectively. The efficiency of the proposed nonlinear optimization methods is demonstrated on several practical exam­ples. The results obtained from the Pratt truss bridge show that the optimum design solution using discrete parameters is 21% lighter than the traditional design with uniform cross sections. Similarly, the results obtained from the 57-bar planar tower truss indicate that the proposed design method using continuous and discrete design parameters can be up to 29% and 9% lighter than traditional design solutions, respectively. Through sensitivity analysis, it is shown that the proposed methodology is robust and leads to significant improvements in convergence rates, which should prove useful in large-scale applications.


First published online: 12 Feb 2016

Keyword : structural optimization, finite element analysis, augmented Lagrangian, quadratic penalty function, hybrid genetics algorithm

How to Cite
Noii, N., Aghayan, I., Hajirasouliha, I., & Kunt, M. M. (2017). A new hybrid method for size and topology optimization of truss structures using modified ALGA and QPGA. Journal of Civil Engineering and Management, 23(2), 252-262. https://doi.org/10.3846/13923730.2015.1075420
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Feb 6, 2017
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This work is licensed under a Creative Commons Attribution 4.0 International License.