Abstract
An algorithm for parametric optimization of steel plane frames is proposed, which is based on a meta-heuristic job search inspired strategy and genetic algorithms using the main and elite populations. A feature of this computational scheme is the ability to effectively solve an optimum problem without introducing penalty functions. This allows us to strictly consider the constraints in any algorithm run. Tension-compression deformations, bending and pure torsion of the rods are taken into account. The goal is to minimize the mass of the frame rods, taking into account active constraints on stresses, displacements and overall stability, including the stability of individual rods. The cross sections of rods vary on discrete sets of admissible options. Analyzing the considered structure’s deformations is performed using the finite-element method in the form of the displacement approach. The constraints on strength and stiffness are checked by iterative calculation of the stress-strain frame state, using a tangential stiffness matrix, which is formed considering the influence of normal forces on the bending of the rods. Information about the convergence of this computational process is required for the stability assessment of the structure. At the elite population formation stage, additional control is carried out on the stability of the frame’s options on the basis of checking the positive definiteness of the tangent stiffness matrix. The efficiency of the proposed approach to the optimal design of frame structures is illustrated by the example of a rod system made of round tubes.
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The study was carried out with the financial support of the RFBR grant No. 18-08-00567.
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Serpik, I. (2020). Parametric Optimization of Steel Frames Using the Job Search Inspired Strategy. In: Murgul, V., Pasetti, M. (eds) International Scientific Conference Energy Management of Municipal Facilities and Sustainable Energy Technologies EMMFT 2018. EMMFT-2018 2018. Advances in Intelligent Systems and Computing, vol 982. Springer, Cham. https://doi.org/10.1007/978-3-030-19756-8_64
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DOI: https://doi.org/10.1007/978-3-030-19756-8_64
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