Structural Engineering and Mechanics

  • 제23권4호
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  • Pages.325-337
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  • 2006
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  • 1225-4568(pISSN)
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  • 1598-6217(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Design and optimization of steel trusses using genetic algorithms, parallel computing, and human-computer interaction

  • Agarwal, Pranab (Department of Civil Engineering, Texas A&M University) ;
  • Raich, Anne M. (Department of Civil Engineering, Texas A&M University)
  • 투고 : 2004.11.29
  • 심사 : 2006.03.14
  • 발행 : 2006.07.10
⟨ 이전 논문 다음 논문 ⟩

초록

A hybrid structural design and optimization methodology that combines the strengths of genetic algorithms, local search techniques, and parallel computing is developed to evolve optimal truss systems in this research effort. The primary objective that is met in evolving near-optimal or optimal structural systems using this approach is the capability of satisfying user-defined design criteria while minimizing the computational time required. The application of genetic algorithms to the design and optimization of truss systems supports conceptual design by facilitating the exploration of new design alternatives. In addition, final shape optimization of the evolved designs is supported through the refinement of member sizes using local search techniques for further improvement. The use of the hybrid approach, therefore, enhances the overall process of structural design. Parallel computing is implemented to reduce the total computation time required to obtain near-optimal designs. The support of human-computer interaction during layout optimization and local optimization is also discussed since it assists in evolving optimal truss systems that better satisfy a user's design requirements and design preferences.

키워드

참고문헌

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피인용 문헌

  1. A Backtracking Search Algorithm for the Simultaneous Size, Shape and Topology Optimization of Trusses vol.13, pp.15, 2016, https://doi.org/10.1590/1679-78253101
  2. Global optimization of trusses with a modified genetic algorithm vol.14, pp.3, 2008, https://doi.org/10.3846/1392-3730.2008.14.10
  3. Optimum design of high-rise steel buildings using an evolution strategy integrated parallel algorithm vol.89, pp.21-22, 2011, https://doi.org/10.1016/j.compstruc.2011.05.019
  4. Large-scale structural optimization using metaheuristic algorithms with elitism and a filter strategy vol.57, pp.2, 2018, https://doi.org/10.1007/s00158-017-1784-3