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Accelerating fuzzy genetic algorithm for the optimization of steel structures

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Abstract

In this paper, the combination of a genetic algorithm and fuzzy logic is used for different types of optimization problems (sizing, topology and geometry) in steel structures. The primary objective is to introduce a new fitness function that uses a real value for the overall satisfaction parameter. By considering a real value instead of a random value for the overall satisfaction parameter, the probability of reaching the global optimum increases. In addition, to decrease the Computation time and to accelerate the convergence rate in the optimization process, a penalty function is added to the fitness function. Also, in spite of the previous methods, fuzzy GA is applied from the first generation of optimization problems. Furthermore, for this process, a similar bilinear membership function is used for the objective function and the constraints. The efficiency and robustness of the proposed approach is demonstrated by several illustrative examples and the results are compared to those of previous studies.

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References

  • Adeli H, Cheng NT (1993) Integrated genetic algorithm for optimization of space structures. J Aerosp Eng, ASCE 6:315–28

    Article  Google Scholar 

  • Adeli H, Kamal O (1986) Efficient optimization of space trusses. Comput Struct 24(3):501–11

    Article  MATH  Google Scholar 

  • Adeli H, Park HS (1998) Neurocomputing for design automation. CRC, Boca Raton

    Google Scholar 

  • Ashtari P, Barzegar F (2009) Topology and sizing optimization of braced steel structures by genetic algorithm. Cairo (Egypt): Thirteenth International Conference on Structural and Geotechnical Engineering 783–90

    Google Scholar 

  • Ashtari P, Barzegar F (2010) Topology and sizing optimization of braced steel structures by an augmented Lagrange method using genetic algorithm. Kuching, Sarawak (Malaysia): Conference on Engineering and Technology Education

    Google Scholar 

  • Bellman RE, Zadeh LA (1970) Decision-making in a fuzzy environment. Manage Sci 17:141–64

    Article  MathSciNet  Google Scholar 

  • Coello Coello CA (2000) Use of a self-adaptive penalty approach for engineering optimization problems. Comput Ind 41:113–27

    Article  Google Scholar 

  • Deb K (1991) Optimal design of a welded beam via genetic algorithms. AIAA J 29(11):2013–15

    Article  Google Scholar 

  • Goldberg DE (1985) Genetic algorithms in search, optimization and machine learning. MA: Addison-Wesley

    Google Scholar 

  • Hajela P, Lee E (1995) Genetic algorithms in truss topological optimization. J Solids Structures 32(22):3341–57

    Article  MATH  MathSciNet  Google Scholar 

  • Hwang SF, He RS (2006) A hybrid real-parameter genetic algorithm for function optimization. Adv Eng Infor 20(1):7–21

    Article  Google Scholar 

  • Kaveh A, Kalatjari V (2003) Topology optimization of trusses using genetic algorithm force method and graph theory. Int J Numer Methods Eng 58(5):771–91

    Article  MATH  Google Scholar 

  • Kawamura H, Ohmori H and Kito N (2002) Truss topology optimization by a modified genetic algorithm. J Struct Multidisc Optim 23:467–473

    Article  Google Scholar 

  • Ragsdell KM, Phillips DT (1976) Optimal design of a class of welded structures using geometric programming. J Engineering for Industries, ASME 98(3):1021–1025, Series B

    Article  Google Scholar 

  • Rahami H, Kaveh A, Gholipour Y (2008) Sizing, geometry and topology optimization of trusses via force method and genetic algorithm. Eng Struct 30(9):2360–69

    Article  Google Scholar 

  • Rajan SD (1995) Sizing, shape and topology optimization of trusses using genetic algorithm. J Struct Eng 121(10):1480–7

    Article  Google Scholar 

  • Sarma KC, Adeli H (2000) Fuzzy genetic algorithm for optimization of steel structures. J Struct Eng, ASCE 126(5):596–604

    Article  Google Scholar 

  • Siddall JN (1972) Analytical design-making in engineering design. Prentice-Hall

  • Soh CK, Yang J (1996) Fuzzy controlled genetic algorithm search for shape optimization. J Comput Civil Eng, ASCE 10(2):143–150

    Article  Google Scholar 

  • Tang W, Tong L, Gu Y (2005) Improved genetic algorithm for design optimization of truss structures with sizing, shape and topology variables. Int J Numer Methods Engrg 62:1737–62

    Article  MATH  Google Scholar 

  • Wang SY, Tai K (2004) Graph representation for structural topology optimization using genetic algorithms. Comput Struct 82(20–21):1609–22

    Article  MathSciNet  Google Scholar 

  • Woon SY, Querin OM, Steven GP (2001) Structural application of a shape optimization method based on a genetic algorithm. J Struct Multidisc Optim 22:57–64

    Article  Google Scholar 

  • Wu SJ, Chow PT (1995) Integrated discrete and configuration optimization of trusses using genetic algorithms. Comput Struct 55(4):695–702

    Article  MATH  Google Scholar 

  • Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338–53

    Article  MATH  MathSciNet  Google Scholar 

  • Zimmermann H-J (1978) Fuzzy programming and linear programming with several objective functions. Fuzzy Sets Syst 1(1):45–55

    Article  MATH  Google Scholar 

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Authors and Affiliations

  1. University of Zanjan, Zanjan, Iran

    Payam Ashtari & Farshid Barzegar

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  1. Payam Ashtari
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  2. Farshid Barzegar
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Correspondence to Payam Ashtari.

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Ashtari, P., Barzegar, F. Accelerating fuzzy genetic algorithm for the optimization of steel structures. Struct Multidisc Optim 45, 275–285 (2012). https://doi.org/10.1007/s00158-011-0700-5

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  • DOI: https://doi.org/10.1007/s00158-011-0700-5

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