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Erschienen in: Structural and Multidisciplinary Optimization 4/2020

01.04.2020 | Research Paper

Topology optimization of nonlinear single-layer domes by an improved electro-search algorithm and its performance analysis using statistical tests

verfasst von: Amin Bigham, Saeed Gholizadeh

Erschienen in: Structural and Multidisciplinary Optimization | Ausgabe 4/2020

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Abstract

In this paper, an improved electro-search algorithm is proposed to solve topology optimization problem of nonlinear single-layer domes. The electro-search algorithm is one of the newly developed metaheuristics inspirited by the movement of electrons around the nucleus of atoms in a molecule. This algorithm exhibits a good performance in solving optimization problems of benchmark functions. However, this algorithm cannot present appropriate performance in tackling discrete structural optimization problems. In the proposed improved algorithm, to reduce the probability of getting stuck in local minima, one electron is assigned to each nucleus and a new equation is defined to determine its orbital’s radius. Moreover, a new scheme is developed to update the position of nuclei in design space. In addition, in order to increase the convergence speed, a memory containing some historically best solutions is added to the algorithm. Parametric and nonparametric statistical tests are applied to analyze the performance of the algorithms. The numerical results are presented in two parts including size optimization of benchmark steel structures and topology optimization problems of single-layer domes. The results demonstrate that the proposed improved algorithm is superior over other well-known metaheuristic algorithms in terms of optimum solution, convergence rate, and overall performance.

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Literatur
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Metadaten
Titel
Topology optimization of nonlinear single-layer domes by an improved electro-search algorithm and its performance analysis using statistical tests
verfasst von
Amin Bigham
Saeed Gholizadeh
Publikationsdatum
01.04.2020
Verlag
Springer Berlin Heidelberg
Erschienen in
Structural and Multidisciplinary Optimization / Ausgabe 4/2020
Print ISSN: 1615-147X
Elektronische ISSN: 1615-1488
DOI
https://doi.org/10.1007/s00158-020-02578-4

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