Skip to main content
Log in

A multi-stage particle swarm for optimum design of truss structures

  • Original Article
  • Published:
Neural Computing and Applications Aims and scope Submit manuscript

Abstract

The contribution of this study is to propose a multi-stage particle swarm optimization (MSPSO) for structural optimization. In this paper, three auxiliary improving mechanisms are added to the standard particle swarm optimization (PSO) in order to enhance its efficiency and reliability dealing with optimum design of truss structures. These mechanisms effectively accelerate the convergence rate of the PSO and also make it robust to attain better optimum solutions during various runs of the algorithm. The effectiveness of the MSPSO is illustrated by several benchmark structural optimization problems. Results demonstrate the efficiency and robustness of the proposed MSPSO algorithm compared to the standard version of the PSO.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Kaveh A, Talatahari S (2010) Optimal design of skeletal structures via the charged system search algorithm. Struct Multidiscip Optim 41:893–911

    Article  Google Scholar 

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

    Article  Google Scholar 

  3. Camp C, Bichon BJ (2003) Design of space trusses using ant colony optimization. J Struct Eng 130(5):741–751

    Article  Google Scholar 

  4. Kaveh A, Talatahari S (2010) Charged system search for optimum grillage systems design using the LRFD–AISC code. J Constr Steel Res 66(6):767–771

    Article  Google Scholar 

  5. Kaveh A, Talatahari S (2012) Charged system search for optimal design of frame structures. Appl Soft Comput 12(1):382–393

    Article  Google Scholar 

  6. Kaveh A, Talatahari S (2011) An enhanced charged system search for configuration optimization using the concept of fields of forces. Struct Multidiscip Optim 43(3):339–351

    Article  Google Scholar 

  7. Lee KS, Geem ZW (2004) A new structural optimization method based on the harmony search algorithm. Comput Struct 82(9–10):781–798

    Article  Google Scholar 

  8. Gandomi AH, Yang X-S, Talatahari S, Deb S (2012) Design optimization of truss structures using cuckoo search algorithm. Struct Des Tall Spec Build. doi:10.1002/tal.1033

    Google Scholar 

  9. Gandomi AH, Yang X-S, Alavi AH, Talatahari S (2012) Bat algorithm for constrained optimization tasks. Neural Comput Appl. doi:10.1007/s00521-012-1028-9

    Google Scholar 

  10. Gandomi AH, Alavi AH (2012) Krill herd: a new bio-inspired optimization algorithm. Commun Nonlinear Sci Numer Simulat. doi:10.1016/j.cnsns.2012.05.010

    MathSciNet  Google Scholar 

  11. Kaveh A, Talatahari S (2010) Optimum design of skeletal structures using imperialist competitive algorithm. Comput Struct 88(21–22):1220–1229

    Article  Google Scholar 

  12. Talatahari S, Kaveh A, Sheikholeslami R (2012) Chaotic imperialist competitive algorithm for optimum design of truss structures. Struct Multidiscip Optim. doi:10.1007/s00158-011-0754-4

    Google Scholar 

  13. Kaveh A, Talatahari S (2009) Size optimization of space trusses using big bang–big crunch algorithm. Comput Struct 87(17–18):1129–1140

    Article  Google Scholar 

  14. Gandomi AH, Yang XS, Alavi AH (2011) Mixed variable structural optimization using firefly algorithm. Comput Struct 89(23–24):2325–2336

    Article  Google Scholar 

  15. Gandomi AH, Yang XS, Talatahari S, Alavi AH (2012) Firefly algorithm with chaos. Commun Nonlinear Sci Numer Simulat. doi:10.1016/j.cnsns.2012.06.009

    Google Scholar 

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

    Article  Google Scholar 

  17. Kaveh A, Talatahari S (2009) 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 

  18. Fourie PC, Groenwold AA (2002) The particle swarm optimization algorithm in size and shape optimization. Struct Multidiscip Optim 23:259–267

    Article  Google Scholar 

  19. Hadidi A, Kaveh A, Farahnadazar B, Talatahari S, Farahmandpour C (2011) An efficient hybrid algorithm based on particle swarm and simulated annealing for optimal design of space trusses. Int J Optim Civ Eng 1(3):377–395

    Google Scholar 

  20. Li LJ, Huang ZB, Liu F, Wu QH (2007) A heuristic particle swarm optimizer for optimization of pin connected structures. Comput Struct 85(7–8):340–349

    Article  Google Scholar 

  21. Schutte JF, Groenwold AA (2003) Sizing design of truss structures using particle swarms. Struct Multidiscip Optim 25:261–269

    Article  Google Scholar 

  22. Kaveh A, Talatahari S (2008) A hybrid particle swarm and ant colony optimization for design of truss structures. Asian J Civ Eng 9(4):329–348

    Google Scholar 

  23. Coello CAC (2002) Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art. Comput Methods Appl Mech Eng 191(11–12):1245–1287

    Article  MATH  Google Scholar 

  24. Michalewicz Z (1995) A survey of constraint handling techniques in evolutionary computation methods. In: 4th annual conference on evolutionary programming. MIT Press, Cambridge, pp 135–155

  25. Kennedy J, Eberhart RC (1995) Particle swarm optimization. IEEE Int Conf Neural Netw 4:1942–1948

    Google Scholar 

  26. 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, pp 39–43

  27. Eberhart RC, Shi Y (2000) Comparing inertia weights and constriction factors in particle swarm optimization. In: Proceedings of the 2000 congress on evolutionary computation, pp 84–88

  28. Venter G, Sobieszczanski-Sobieski J (2002) Particle swarm optimization. In: Proceedings of the 43rd AIAA/ASME/ASCE/AHS/ASC structures, structural dynamics, and materials (conference held in Denver, CO)

  29. Vanderplaats GN (1999) Numerical optimization techniques for engineering design, 3rd edn. Vanderplaats Research and Development, Colorado Springs

    Google Scholar 

  30. Vandenbergh F, Engelbrecht AP (2006) A study of particle swarm optimization particle trajectories. Inf Sci 176:937–971

    Article  MathSciNet  Google Scholar 

  31. Camp C, Pezeshk S, Cao G (1998) Optimized design of two dimensional structures using genetic algorithm. J Struct Eng 124(5):551–559

    Article  Google Scholar 

  32. Khan MR, Wilmert KD, Thronton WA (1979) An optimality criterion method for large-scale structures. Am Inst Aeronaut Astronaut J 17(7):753–761

    Article  Google Scholar 

  33. Sheu CY, Schmit LA Jr (1972) Minimum weight design of elastic redundant trusses under multiple static load conditions. AIAA 10(2):155–162

    Article  Google Scholar 

  34. Gandomi AH, Yang XS (2011) Benchmark problems in structural optimization. In: Koziel S, Yang XS (eds) Computational optimization, methods and algorithms, chap 12, vol 356. Springer, Berlin, pp 259–281

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to S. Talatahari.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Talatahari, S., Kheirollahi, M., Farahmandpour, C. et al. A multi-stage particle swarm for optimum design of truss structures. Neural Comput & Applic 23, 1297–1309 (2013). https://doi.org/10.1007/s00521-012-1072-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00521-012-1072-5

Keywords

Navigation