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Optimal design of skeletal structures via the charged system search algorithm

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Abstract

A new meta-heuristic optimization algorithm is presented for design of skeletal structures. The algorithm is inspired by the Coulomb and Gauss’s laws of electrostatics in physics, and it is called charged system search (CSS). CSS utilizes a number of charged particle (CP) which affects each other based on their fitness values and separation distances considering the governing laws of Coulomb and Gauss from electrical physics and the governing laws of motion from the Newtonian mechanics. Some truss and frame structures are optimized with the CSS algorithm. Comparison of the results of the CSS with those of other meta-heuristic algorithms shows the robustness of the new algorithm.

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References

  • American Institute of Steel Construction (AISC) (1989) Manual of steel construction-allowable stress design, 9th edn. American Institute of Steel Construction, Chicago

    Google Scholar 

  • ASCE 7-05 (2005) Minimum design loads for building and other structures

  • Dorigo M, Maniezzo V, Colorni A (1996) The ant system: optimization by a colony of cooperating agents. IEEE Trans Sys Man Cybern, B 26(1):29–41

    Article  Google Scholar 

  • Eberhart RC, Kennedy J (1995) A new optimizer using particle swarm theory. In: Proceedings of the sixth international symposium on micro machine and human science, Nagoya, Japan

  • Erol OK, Eksin I (2006) New optimization method: Big Bang–Big Crunch. Adv Eng Softw 37:106–111

    Article  Google Scholar 

  • Fogel LJ, Owens AJ, Walsh MJ (1966) Artificial intelligence through simulated evolution. Wiley, Chichester

    MATH  Google Scholar 

  • Geem ZW (2000) Optimal design of water distribution networks using harmony search. PhD thesis, Korea University, South Korea

    Google Scholar 

  • Goldberg DE (1989) Genetic algorithms in search optimization and machine learning. Addison-Wesley, Boston

    MATH  Google Scholar 

  • Glover F (1977) Heuristic for integer programming using surrogate constraints. Decis Sci 8(1):156–166

    Article  Google Scholar 

  • Halliday D, Resnick R, Walker J (2008) Fundamentals of physics, 8th edn. Wiley, New York

    Google Scholar 

  • Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor

    Google Scholar 

  • Kaveh A, Farahmand Azar B, Talatahari S (2008) Ant colony optimization for design of space trusses. Int J Space Struct 23(3):167–181

    Article  Google Scholar 

  • Kaveh A, Talatahari S (2009a) An improved ant colony optimization for constrained engineering design problems. Eng Comput (in press)

  • Kaveh A, Talatahari S (2009b) A novel heuristic optimization method: charged system search. Acta Mech. doi:10.1007/s00707-009-0270-4

    Google Scholar 

  • Kaveh A, Talatahari S (2009c) Particle swarm optimizer, ant colony strategy and harmony search scheme hybridized for optimization of truss structures. Comput Struct 87(5–6):267–283

    Article  Google Scholar 

  • Kaveh A, Talatahari S (2009d) A particle swarm ant colony optimization for truss structures with discrete variables. J Constr Steel Res 65(8–9):1558–1568

    Article  Google Scholar 

  • Kaveh A, Talatahari S (2009e) Size optimization of space trusses using Big Bang–Big Crunch algorithm. Comput Struct 87:1129–1140

    Article  Google Scholar 

  • Kirkpatrick S, Gelatt C, Vecchi M (1983) Optimization by simulated annealing. Science 220(4598):671–680

    Article  MathSciNet  Google Scholar 

  • Lee KS, Geem ZW (2004) A new structural optimization method based on the harmony search algorithm. Comput Struct 82:781–798

    Article  Google Scholar 

  • Rajeev S, Krishnamoorthy CS (1992) Discrete optimization of structures using genetic algorithms. J Struct Eng ASCE 118(5):1233–1250

    Article  Google Scholar 

  • Saka MP, Hasançebi O (2009) Design code optimization of steel structures using adaptive harmony search algorithm, chapter 3. In: Geem ZW (ed) Harmony search algorithms for structural design. Springer, Berlin

    Google Scholar 

  • Schutte JJ, Groenwold AA (2003) Sizing design of truss structures using particle swarms. Struct Multidisc Optim 25:261–269

    Article  Google Scholar 

Download references

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Correspondence to Ali Kaveh.

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Kaveh, A., Talatahari, S. Optimal design of skeletal structures via the charged system search algorithm. Struct Multidisc Optim 41, 893–911 (2010). https://doi.org/10.1007/s00158-009-0462-5

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  • DOI: https://doi.org/10.1007/s00158-009-0462-5

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