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Optimal Design of Pitched Roof Rigid Frames with Non-Prismatic Members Using Quantum Evolutionary Algorithm

Author(s):


Medium: journal article
Language(s): English
Published in: Periodica Polytechnica Civil Engineering
DOI: 10.3311/ppci.14091
Abstract:

The weight and shape of the gable and multi-span frames (mono and two-span pitched roof) with tapered members, as a familiar group of the pitched roof frames, are highly dependent on the properties of the member cross-section. In this work a quantum inspired evolutionary algorithms, so-called Quantum evolutionary algorithm (QEA) [1], are utilized for optimal design of one gable frame and a multi-span frame in five alternatives with tapered members. In order to optimize the frames, the design is performed using the AISC speciļ¬cations for stress, displacement and stability constraints. The design constraints and weight of the gable and multi-span frames are computed from the cross-section of members. These optimum weights are obtained using aforementioned optimization algorithm considering the cross-section of members and design constraints as optimization variables and constraints, respectively. A comparative study of the QEA and some recently developed methods from literature is also performed to illustrate the performance of the utilized optimization algorithm and its featuring. Furthermore, optimal design of a multi-span frame is compared with the solution of other methods including the same conditions and constraints. This study indicates the power of QEA in exploring and exploitation due the search space with using Q-gate and binary code for individual representation and updating. Binary code helps the QEA to find optimal solution even with minimum number of Q-bit individuals. High speed of this method is because of such a feature.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.3311/ppci.14091.
  • About this
    data sheet
  • Reference-ID
    10536475
  • Published on:
    01/01/2021
  • Last updated on:
    26/02/2021
 
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