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  • Truss optimization with natural frequency bounds using improved symbiotic organisms search

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    MirjaliliPUB4853.pdf (894.7Kb)
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    Accepted Manuscript (AM)
    Author(s)
    Tejani, Ghanshyam G
    Saysani, Vimal J
    Patel, Vivek K
    Mirjalili, Seyedali
    Griffith University Author(s)
    Mirjalili, Seyedali
    Year published
    2018
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    Abstract
    Many engineering structures are subjected to dynamic excitation, which may lead to undesirable vibrations. The multiple natural frequency bounds in truss optimization problems can improve dynamic behaviour of structures. However, shape and size variables with frequency bounds are challenging due to its characteristic, which is non-linear, non-convex, and implicit with respect to the design variables. As the main contribution, this work proposes an improved version of a recently proposed Symbiotic Organisms Search (SOS) called an Improved SOS (ISOS) to tackle the above-mentioned challenges. The main motivation is to improve ...
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    Many engineering structures are subjected to dynamic excitation, which may lead to undesirable vibrations. The multiple natural frequency bounds in truss optimization problems can improve dynamic behaviour of structures. However, shape and size variables with frequency bounds are challenging due to its characteristic, which is non-linear, non-convex, and implicit with respect to the design variables. As the main contribution, this work proposes an improved version of a recently proposed Symbiotic Organisms Search (SOS) called an Improved SOS (ISOS) to tackle the above-mentioned challenges. The main motivation is to improve the exploitative behaviour of SOS since this algorithm significantly promotes exploration which is a good mechanism to avoid local solution, yet it negatively impacts the accuracy of solutions (exploitation) as a consequence. The feasibility and effectiveness of ISOS is studied with six benchmark planar/space trusses and thirty functions extracted from the CEC2014 test suite, and the results are compared with other meta-heuristics. The experimental results show that ISOS is more reliable and efficient as compared to the basis SOS algorithm and other state-of-the-art algorithms.
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    Journal Title
    Knowledge-Based Systems
    Volume
    143
    DOI
    https://doi.org/10.1016/j.knosys.2017.12.012
    Copyright Statement
    © 2018 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
    Subject
    Structural engineering
    Psychology
    Publication URI
    http://hdl.handle.net/10072/372938
    Collection
    • Journal articles

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