iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://doi.org/10.1007/s00366-019-00744-x
Optimal design of truss structures using weighted superposition attraction algorithm | Engineering with Computers Skip to main content
Springer Nature Link
Log in

Optimal design of truss structures using weighted superposition attraction algorithm

  • Original Article
  • Published:
Engineering with Computers Aims and scope Submit manuscript

Abstract

In this paper, a recently developed swarm based metaheuristic algorithm called weighted superposition attraction (WSA) is implemented for sizing optimization of truss structures first time in literature. The WSA algorithm based on superposition and attracted movement of agents that are observable in many natural systems. The efficiency and robustness of the WSA are investigated by solving five classic 2D and 3D truss-weight minimization problems with fixed-geometry and up to 200 elements. Optimization results demonstrated that WSA is able to generate the best results in terms of optimized weight, standard deviation and number of structural analyses in comparison to all other compared state-of-the-art metaheuristic algorithms.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  1. Bianchi L, Dorigo M, Gambardella LM, Gutjahr WJ (2009) A survey on metaheuristics for stochastic combinatorial optimization. Nat Comput 8:239–287

    MathSciNet  MATH  Google Scholar 

  2. Yang XS (2010) Engineering optimization an introduction with metaheuristic applications. Wiley, Hoboken

    Google Scholar 

  3. Adeli H, Cheng NT (1994) Concurrent genetic algorithms for optimization of large structures. J Aerosp Eng 7(3):276–296

    Google Scholar 

  4. Deb K, Gulati S (2001) Design of truss-structures for minimum weight using genetic algorithms. Finite Elem Anal Des 37:447–465

    MATH  Google Scholar 

  5. 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 Eng 62(13):1737–1762

    MATH  Google Scholar 

  6. Hasancebi O, Erbatur F (2002) On efficient use of simulated annealing in complex structural optimization problems. Acta Mech 157(1–4):27–50

    MATH  Google Scholar 

  7. Couceiro I, Paris J, Martinez S, Colominas I, Navarrina F, Casteleiro M (2016) Structural optimization of lattice steel transmission towers. Eng Struct 117:274–286

    Google Scholar 

  8. Hasancebi O, Tort C, Sahin S (2017) Optimum design of steel lattice transmission line towers using simulated annealing and PLS-TOWER. Comput Struct 179:75–94

    Google Scholar 

  9. Lamberti L (2008) An efficient simulated annealing algorithm for design optimization of truss structures. Comput Struct 86(19–20):1936–1953

    Google Scholar 

  10. Camp CV, Bichon BJ (2004) Design of space trusses using ant colony optimization. J Struct Eng 130(5):741–751

    Google Scholar 

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

    Google Scholar 

  12. Camp CV (2007) Design of space trusses using big bang–big crunch optimization. J Struct Eng 133(7):999–1008

    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

    Google Scholar 

  14. Perez RE, Behdinan K (2007) Particle swarm approach for structural design optimization. Comput Struct 85(19–20):1579–1588

    Google Scholar 

  15. 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

    Google Scholar 

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

    Google Scholar 

  17. Talatahari S, Kheirollahi M, Farahmandpour C, Gandomi AH (2013) A multi-stage particle swarm for optimum design of truss structures. Neural Comput Appl 23(5):1297–1309

    Google Scholar 

  18. Kaveh A, Ilchi Ghazaan M (2017) Optimum design of skeletal structures using PSO-Based algorithms. Period Polytech Civ Eng 61(2):184

    Google Scholar 

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

    MATH  Google Scholar 

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

    Google Scholar 

  21. Sonmez M (2011) Artificial bee colony algorithm for optimization of truss structures. Appl Soft Comput 11(2):2406–2418

    MathSciNet  Google Scholar 

  22. Degertekin SO (2012) Improved harmony search algorithms for sizing optimization of truss structures. Comput Struct 92–93:229–241

    Google Scholar 

  23. Degertekin SO, Hayalioglu MS (2013) Sizing truss structures using teaching–learning-based optimization. Comput Struct 119:177–188

    Google Scholar 

  24. Camp CV, Farshchin M (2014) Design of space trusses using modified teaching–learning based optimization. Eng Struct 62–63:87–97

    Google Scholar 

  25. Kaveh A, Khayatazad M (2012) A new meta-heuristic method: ray optimization. Comput Struct 112:283–294

    Google Scholar 

  26. Kaveh A, Khayatazad M (2013) Ray optimization for size and shape optimization of truss structures. Comput Struct 117:82–94

    Google Scholar 

  27. Kaveh A, Ilchi Ghazaan M, Bakhshpoori T (2013) An improved ray optimization algorithm for design of truss structures. Period Polytech Civ Eng 57:97–112

    Google Scholar 

  28. Kaveh A, Bakhshpoori T (2013) Optimum design of space trusses using cuckoo search algorithm with levy flights. Iran J Sci Technol Trans B Eng 37:1–15

    Google Scholar 

  29. Kaveh A, Sheikholeslami R, Talatahari S, Keshvari-Ilkhichi M (2014) Chaotic swarming of particles: a new method for size optimization of truss structures. Adv Eng Softw 67:136–147

    Google Scholar 

  30. Kaveh A, Mahdavi VR (2014) Colliding bodies optimization method for optimum design of truss structures with continuous variables. Adv Eng Softw 70:1–12

    Google Scholar 

  31. Kaveh A, Mahdavi VR (2014) Colliding bodies optimization: a novel meta-heuristic method. Comput Struct 139:18–27

    Google Scholar 

  32. Kaveh A, Ilchi Ghazaan M (2014) Enhanced colliding bodies optimization for design problems with continuous and discrete variables. Adv Eng Softw 77:66–75

    Google Scholar 

  33. Kaveh A, Bakhshpoori T, Afshari E (2014) An efficient hybrid particle swarm and swallow swarm optimization algorithm. Comput Struct 143:40–59

    Google Scholar 

  34. Jalili S, Hosseinzadeh Y (2015) A cultural algorithm for optimal design of truss structures. Latin Am J Solids Struct 12(9):1721–1747

    Google Scholar 

  35. Bekdas G, Nigdeli SM, Yang XS (2015) Sizing optimization of truss structures using flower pollination algorithm. Appl Soft Comput 37:322–331

    Google Scholar 

  36. Kaveh A, Bakhshpoori T (2016) A new metaheuristic for continuous structural optimization: water evaporation optimization. Struct Multidiscip Optim 54(1):23–43

    Google Scholar 

  37. Degertekin SO, Lamberti L, Hayalioglu MS (2017) Heat transfer search algorithm for sizing optimization of truss structures. Latin Am J Solids Struct 14(3):373–397

    Google Scholar 

  38. Kaveh A, Zolghadr A (2017) Cyclical parthenogenesis algorithm: a new meta-heuristic algorithm. Asian J Civ Eng 18(5):673–701

    Google Scholar 

  39. Degertekin SO, Lamberti L, Ugur IB (2017) Sizing, layout and topology design optimization of truss structures using the Jaya algorithm. Appl Soft Comput. https://doi.org/10.1016/j.asoc.2017.10.001(in press)

    Article  Google Scholar 

  40. Kaveh A, Zakian P (2018) Improved GWO algorithm for optimal design of truss structures. Eng Comput. https://doi.org/10.1007/s00366-017-0567-1

    Article  Google Scholar 

  41. Aslani M, Ghasemi P, Gandomi AH (2018) Constrained mean-variance mapping optimization for truss optimization problems. Struct Des Tall Spec Build 27(6):1449

    Google Scholar 

  42. Khatibinia M, Yazdani H (2018) Accelerated multi-gravitational search algorithm for size optimization of truss structures. Swarm Evolut Comput 38:109–119

    Google Scholar 

  43. Talatahari S, Gandomi AH, Yun GJ (2014) Optimum design of tower structures using firefly algorithm. Struct Des Tall Spec Build 23(5):350–361

    Google Scholar 

  44. Lamberti L, Pappalettere C (2011) Metaheuristic design optimization of skeletal structures: a review. Comput Technol Rev 4:1–32

    Google Scholar 

  45. Saka MP, Dogan E (2012) Recent developments in metaheuristic algorithms: are view. Comput Technol Rev 5:31–78

    Google Scholar 

  46. Sorensen K, Sevaux M, Glover F (2017) A history of metaheuristics. In: Marti R, Pardalo P, Resende M (eds) Handbook of heuristics. Springer, New York

    Google Scholar 

  47. Baykasoğlu A, Senol ME (2016) Opposition-based weighted superposition attraction algorithm for travelling salesman problems, XIV. In: International logistics and supply chain congress, Izmir, Turkey, pp 314–319. ISBN:978-605-338-186-0

  48. Baykasoğlu A, Senol ME (2016) Combinatorial optimization via weighted superposition attraction, OR2016: annual International Conference of the German Operations Research Society, Hamburg, Germany. Helmut-Schmidt-Universität/Universität der Bundeswehr Hamburg, Germany, p 82

  49. Baykasoğlu A, Akpinar S (2017) Weighted Superposition Attraction (WSA): a swarm intelligence algorithm for optimization problems—part 1: unconstrained optimization. Appl Soft Comput 56:520–540

    Google Scholar 

  50. Baykasoğlu A, Akpinar S (2015) Weighted superposition attraction (WSA): a swarm intelligence algorithm for optimization problems—Part 2: constrained optimization. Appl Soft Comput 37:396–415

    Google Scholar 

  51. Baykasoğlu A, Özsoydan FB (2018) Dynamic optimization in binary search spaces via weighted superposition attraction algorithm. Expert Syst Appl 96:157–174

    Google Scholar 

  52. Baykasoğlu A, Akpinar S (2018) An improved target point determination procedure for weighted superposition attraction algorithm. Neural Comput Appl (under review)

  53. Baykasoğlu A, Golcuk I, Ozsoydan FB (2018) Improving fuzzy c-means clustering via quantum-enhanced weighted superposition attraction algorithm. Hacet J Math Stat. https://doi.org/10.15672/HJMS.2018.655

    Article  Google Scholar 

  54. Baykasoğlu A (2012) Design optimization with chaos embedded great deluge algorithm. Appl Soft Comput 12(3):1055–1067

    Google Scholar 

  55. Kim TH, Maruta I, Sugie T (2010) A simple and efficient constrained particle swarm optimization and its application to engineering design problems. Proc Inst Mech Eng Part C J Mech Eng Sci 224(2):389–400

    Google Scholar 

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

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Faculty of Engineering, Dokuz Eylül University, Tınaztepe Campus, 35397, Buca, İzmir, Turkey

    Baykasoğlu Adil

  2. Department of Mechanical Engineering, Faculty of Engineering, Hitit University, Çorum, Turkey

    Baykasoğlu Cengiz

Authors
  1. Baykasoğlu Adil
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Baykasoğlu Cengiz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Baykasoğlu Adil.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Adil, B., Cengiz, B. Optimal design of truss structures using weighted superposition attraction algorithm. Engineering with Computers 36, 965–979 (2020). https://doi.org/10.1007/s00366-019-00744-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00366-019-00744-x

Keywords

Search

Navigation