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Genetic Algorithms for Optimization of 3D Truss Structures

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Metaheuristics and Optimization in Civil Engineering

Part of the book series: Modeling and Optimization in Science and Technologies ((MOST,volume 7))

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Abstract

Various optimization techniques have been applied to find the optimum solutions of structural design problems in the last 50 or 60 years. Simple structural optimization problems with continuous design variables have been solved initially using mathematically diverse techniques. New approaches called meta-heuristic techniques have been emerging along with the progress of traditional methods. This chapter first introduces the mathematical formulations of optimization problems and then gives a summary and development process of the preliminary techniques such as genetic algorithm (GA) in obtaining the optimum solutions. The mathematical formulations of the structural optimization problems are associated with the design variables, loads, structural responses, and constraints. Strategies are proposed to improve the performance of the technique to reduce the number of search and the size of the problem. Finally, some examples related to 3D truss structures are presented.

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Authors and Affiliations

  1. Department of Civil Engineering, Karadeniz Technical University, 61080, Trabzon, Turkey

    Vedat Toğan & Ayşe Turhan Daloğlu

Authors
  1. Vedat Toğan
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  2. Ayşe Turhan Daloğlu
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Correspondence to Ayşe Turhan Daloğlu .

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Editors and Affiliations

  1. School of Science and Technology, Middlesex University, London, United Kingdom

    Xin-She Yang

  2. Faculty of Engineering, Istanbul University Faculty of Engineering, Istanbul, Turkey

    Gebrail Bekdaş

  3. Department of Civil Engineering, Istanbul University, Istanbul, Turkey

    Sinan Melih Nigdeli

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Toğan, V., Daloğlu, A.T. (2016). Genetic Algorithms for Optimization of 3D Truss Structures. In: Yang, XS., Bekdaş, G., Nigdeli, S. (eds) Metaheuristics and Optimization in Civil Engineering. Modeling and Optimization in Science and Technologies, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-319-26245-1_6

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  • DOI: https://doi.org/10.1007/978-3-319-26245-1_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26243-7

  • Online ISBN: 978-3-319-26245-1

  • eBook Packages: EngineeringEngineering (R0)

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