Structural Engineering and Mechanics

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Optimum design of steel space structures using social spider optimization algorithm with spider jump technique

  • Aydogdu, Ibrahim (Department of Civil Engineering, Akdeniz University) ;
  • Efe, Perihan (Department of Civil Engineering, Balikesir University) ;
  • Yetkin, Metin (Department of Civil Engineering, Balikesir University) ;
  • Akin, Alper (Trinity Meyer Utility Structures)
  • Received : 2016.08.28
  • Accepted : 2017.03.15
  • Published : 2017.05.10
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Abstract

In this study, recently developed swarm intelligence algorithm called Social Spider Optimization (SSO) approach and its enhanced version of SSO algorithm with spider jump techniques is used to develop a structural optimization technique for steel space structures. The improved version of SSO uses adaptive randomness probability in generating new solutions. The objective function of the design optimization problem is taken as the weight of a steel space structure. Constraints' functions are implemented from American Institute of Steel Construction-Load Resistance factor design (AISC-LRFD) and Ad Hoc Committee report and practice which cover strength, serviceability and geometric requirements. Three steel space structures are optimized using both standard SSO and SSO with spider jump (SSO_SJ) algorithms and the results are compared with those available in the literature in order to investigate the performance of the proposed algorithms.

Keywords

References

  1. Akin, A. and Aydogdu, I. (2015), "Optimum design of steel space frames by hybrid teaching-learning based optimization and harmony search algorithms", Int. J. Mech. Aerosp. Indus. Mech. Manuf. Eng., 9(7), 1367-1374.
  2. Alqedra, M., Khalifa, A. and Arafa, M. (2015), "An intelligent tuned harmony search algorithm for optimum design of steel framed structures to AISC-LRFD", Adv. Res., 4(6), 421-440. https://doi.org/10.9734/AIR/2015/16831
  3. Arafa, M., Khalifa, A. and Alqedra, M. (2016), "Design optimization of semi-rigidly connected steel frames using harmony search algorithm", J. Eng. Res. Technol., 2(2), 95-104.
  4. Artar, M. (2016), "Optimum design of steel space frames under earthquake effect using harmony search", Struct. Eng. Mech., 58(3), 597-612. https://doi.org/10.12989/sem.2016.58.3.597
  5. Artar, M. and Daloglu, A.T. (2015), "The optimization of multi-storey composite steel frames with genetic algorithm including dynamic constraints", Tek Dergi, 26(2), 7077-7098.
  6. Artar, M. and Daloglu, A.T. (2015), "Optimum design of steel frames with semi-rigid connections and composite beams", Struct. Eng. Mech.,55(2), 299-313. https://doi.org/10.12989/sem.2015.55.2.299
  7. Artar, M. and Daloglu, A.T. (2015), "Optimum design of steel space frames with composite beams using genetic algorithm", Steel Compos. Struct., 19(2), 503-519. https://doi.org/10.12989/scs.2015.19.2.503
  8. ASCE (2005), ASCE 7-05, Minimum Design Loads for Buildings and Other Structures, American Society of Civil Engineers, Reston, Virginia, ABD.
  9. Aviles, L. (1986), "Sex-ratio bias and possible group selection in the social spider Anelosimus eximius", Am. Natural., 1-12.
  10. Aydogdu, I. (2017), "Cost optimization of reinforced concrete cantilever retaining walls under seismic loading using a biogeography-based optimization algorithm with Levy flights", Eng. Optim., 49(3), 381-400. https://doi.org/10.1080/0305215X.2016.1191837
  11. Aydogdu, I. and Akin, A. (2014). "Optimum design of geodesic aluminum domes using firefly algorithm", Proceedings of the ACE 2014 11th International Congress on Advances in Civil Engineering, Istanbul, Turkey.
  12. Aydogdu, I. and Saka, M.P. (2009). "Ant colony optimization of irregular steel frames including effect of warping", Proceedings of the Twelfth International Conference on Civil, Structural and Environmental Engineering Computing, Madeira, Portugal.
  13. Aydogdu, I. (2010), "Optimum design of 3-D irregular steel frames using ant colony optimization and harmony search algorithms", PhD Thesis, Middle East Technical University, August, Ankara, Turkey
  14. Aydogdu, I. and Akin, A. (2014), "Teaching and learning-based optimization algorithm for optimum design of steel buildings", Comput. Civil Build. Eng., 2167-2175.
  15. Aydogdu, I., Akin, A. and Saka, M. (2012), Discrete Design Optimization of Space Steel Frames using the Adaptive Firefly Algorithm, Civil Comp, Dubrovnik, Crotia.
  16. Aydogdu, I., Akin, A. and Saka, M. (2012), Optimum Design of Steel Space Frames by Artificial Bee Colony Algorithm, Ankara, Turkey.
  17. Aydogdu, I., Akin, A. and Saka, M. (2016), "Design optimization of real world steel space frames using artificial bee colony algorithm with Levy flight distribution", Adv. Eng. Softw., 92, 1-14. https://doi.org/10.1016/j.advengsoft.2015.10.013
  18. Azad, S.K. and Hasancebi, O. (2013), "Upper bound strategy for metaheuristic based design optimization of steel frames", Adv. Eng. Softw., 57, 19-32. https://doi.org/10.1016/j.advengsoft.2012.11.016
  19. Azad, S.K. and Hasancebi, O. (2014), "An elitist self-adaptive step-size search for structural design optimization", Appl. Soft Comput., 19, 226-235. https://doi.org/10.1016/j.asoc.2014.02.017
  20. Azad, S.K. and Hasancebi, O. (2015), "Computationally efficient discrete sizing of steel frames via guided stochastic search heuristic", Comput. Struct., 156, 12-28. https://doi.org/10.1016/j.compstruc.2015.04.009
  21. Azad, S.K., Hasancebi, O. and Saka, M. (2014), "Guided stochastic search technique for discrete sizing optimization of steel trusses: A design-driven heuristic approach", Comput. Struct., 134, 62-74. https://doi.org/10.1016/j.compstruc.2014.01.005
  22. Burgess, J. and Uetz, G. (1982), "Social spacing strategies in spiders", Spider Communication: Mechanisms and Ecological Significance, 317-351.
  23. Campon, F.F. (2007), "Group foraging in the colonial spider Parawixia bistriata (Araneidae): effect of resource levels and prey size", Animal Behav., 74(5), 1551-1562. https://doi.org/10.1016/j.anbehav.2007.02.030
  24. Carbas, S. and Aydogdu, I. (2017). "Utilization of harmony Search algorithm in optimal structural design of cold-formed steel structures", International Conference on Harmony Search Algorithm.
  25. Cuevas, E., Cienfuegos, M., Zaldivar, D. and Perez-Cisneros, M. (2013), "A swarm optimization algorithm inspired in the behavior of the social-spider", Exp. Syst. Appl., 40(16), 6374-6384. https://doi.org/10.1016/j.eswa.2013.05.041
  26. Carbas, S. (2016), "Design optimization of steel frames using an enhanced firefly algorithm", Eng. Optim., 48(12), 2007-2025. https://doi.org/10.1080/0305215X.2016.1145217
  27. Carbas, S. (2016), "Optimum structural design of spatial steel frames via biogeography-based optimization", Neural Comput. Appl., 1-15.
  28. Degertekin, S.O. (2012), "Optimum design of geometrically non-linear steel frames using artificial bee colony algorithm", Steel Compos. Struct., 12(6), 505-522. https://doi.org/10.12989/scs.2012.12.6.505
  29. Degertekin, S.O. and Hayalioglu, M.S. (2013), "Sizing truss structures using teaching-learning-based optimization", Comput. Struct., 119, 177-188. https://doi.org/10.1016/j.compstruc.2012.12.011
  30. Dorigo, M., Maniezzo, V. and Colorni, A. (1996), "Ant system: optimization by a colony of cooperating agents", Syst. Man Cyber. Part B: Cyber. IEEE Tran., 26(1), 29-41. https://doi.org/10.1109/3477.484436
  31. Elias, D.O., Andrade, M.C. and Kasumovic, M.M. (2011), "Dynamic population structure and the evolution of spider mating systems", Adv. Insect Phys., 41, 65.
  32. Ellingwood, B. (1986), "Structural serviceability: a critical appraisal and research needs", J. Struct. Eng., 112(12), 2646-2664. https://doi.org/10.1061/(ASCE)0733-9445(1986)112:12(2646)
  33. Esapour, K., Hoseinzadeh, R., Akbari-Zadeh, M.R. and Zare, J. (2015), "A new sufficent method based on levy-social spider technique for optimal economic dispatch of thermal power unit", J. Intell. Fuzzy Syst., 28(3), 1137-1143.
  34. Fister, Jr, I., Yang, X.S., Fister, I., Brest, J. and Fister, D. (2013), "A brief review of nature-inspired algorithms for optimization", arXiv preprint arXiv:1307.4186.
  35. Gholizadeh, S. and Poorhoseini, H. (2015), "Optimum design of steel frame structures by a modified dolphin echolocation algorithm", Struct. Eng. Mech., 55(3), 535-554. https://doi.org/10.12989/sem.2015.55.3.535
  36. Hameed, W.I., Kadhim, A.S. and Al-Thuwaynee, A.A.K. (2016), "Field weakening control of a separately excited DC motor using neural network optemized by social spider algorithm", Eng, 8(1), 1. https://doi.org/10.4236/eng.2016.81001
  37. Hasancebi, O. and Azad, S.K. (2015), "Adaptive dimensional search: a new metaheuristic algorithm for discrete truss sizing optimization", Comput. Struct., 154, 1-16. https://doi.org/10.1016/j.compstruc.2015.03.014
  38. Hasancebi, O., Carbas, S., Dogan, E., Erdal, F. and Saka, M.P. (2009), "Performance evaluation of metaheuristic search techniques in the optimum design of real size pin jointed structures", Comput. Struct., 87(5-6), 284-302. https://doi.org/10.1016/j.compstruc.2009.01.002
  39. Holldobler, B., Wilson, E.O., Keller, L., Gordon, E., Bisseleua, B., Vidal, S., Bos, M., Tylianakis, J., Steffan-Dewenter, I. and Tscharntke, T. (1994), Journey to the Ants: a Story of Scientific Exploration, CATIE, Turrialba. (Costa Rica)
  40. Jones, T.C. and Riechert, S.E. (2008), "Patterns of reproductive success associated with social structure and microclimate in a spider system", Animal Behav., 76(6), 2011-2019. https://doi.org/10.1016/j.anbehav.2008.07.033
  41. Karaboga, D. (2005), "An Idea based on honey bee swarm for numerical optimization", Technical Report-tr06, Engineering Faculty, Computer Engineering Department, Erciyes University.
  42. Kassabalidis, I., El-Sharkawi, M.A., Marks, R.J., Arabshahi, P. and Gray, A.A. (2001). "Swarm intelligence for routing in communication networks", Global Telecommunications Conference, GLOBECOM'01, IEEE.
  43. Kavousi-Fard, A., Abbasi, A., Rostami, M.A. and Khosravi, A. (2015), "Optimal distribution feeder reconfiguration for increasing the penetration of plug-in electric vehicles and minimizing network costs", Energy, 93, 1693-1703. https://doi.org/10.1016/j.energy.2015.10.055
  44. Kennedy, J., Kennedy, J.F., Eberhart, R.C. and Shi, Y. (2001), Swarm Intelligence, Morgan Kaufmann.
  45. Khorramnia, R., Akbarizadeh, M.R., Jahromi, M.K., Khorrami, S.K. and Kavusifard, F. (2015), "A new unscented transform for considering wind turbine uncertainty in ED problem based on SSO algorithm", J. Intell. Fuzzy Syst., 29(4), 1479-1491. https://doi.org/10.3233/IFS-151627
  46. LRFD, A. (2000), "Load & Resistance Factor Design Specification", American Institute of Steel Construction, Chicago, Illinois.
  47. Lubin, Y. and Bilde, T. (2007), "The evolution of sociality in spiders", Adv. Study Behav., 37, 83-145.
  48. Mirjalili, S.Z., Saremi, S. and Mirjalili, S.M. (2015), "Designing evolutionary feedforward neural networks using social spider optimization algorithm", Neural Comput. Appl., 26(8), 1919-1928. https://doi.org/10.1007/s00521-015-1847-6
  49. Oster, G.F. and Wilson, E.O. (1978), Caste and Ecology in the Social Insects, Princeton University Press
  50. Pasquet, A. and Krafft, B. (1992), "Cooperation and prey capture efficiency in a social spider, Anelosimus eximius (Araneae, Theridiidae)", Ethology, 90(2), 121-133. https://doi.org/10.1111/j.1439-0310.1992.tb00826.x
  51. Passino, K.M. (2002), "Biomimicry of bacterial foraging for distributed optimization and control", Control Syst., IEEE, 22(3), 52-67. https://doi.org/10.1109/MCS.2002.1004010
  52. Pereira, D.R., Delpiano, J. and Papa, J.P. (2015), "On the optical flow model selection through metaheuristics", Eurasip. J. Image Vide, 2015(1), 11. https://doi.org/10.1186/s13640-015-0066-5
  53. Rao, S.S. (2009), Engineering Optimization: Theory and Practice, John Wiley & Sons, Canada.
  54. Rypstra, A.L. and Tirey, R.S. (1991), "Prey size, prey perishability and group foraging in a social spider", Oecologia, 86(1), 25-30. https://doi.org/10.1007/BF00317384
  55. Saka, M.P. (2003), Optimum Design of Skeletal Structures: A Review, Saxe-Coburg Publications, Stirlingshire, UK.
  56. Saka, M.P. (2007), Optimum Design of Steel Frames using Stochastic Search Techniques Based on Natural Phenomena: A Review
  57. Saka, M.P. (2014), "Shape and topology optimization design of skeletal structures using metaheuristic algorithms: a review", Comput. Tech. Rev., 9, 31-68. https://doi.org/10.4203/ctr.9.2
  58. Saka, M.P., Carbas, S., Aydogdu, I. and Akin, A. (2016), Use of Swarm Intelligence in Structural Steel Design Optimization, Springer
  59. Saka, M.P., Dogan, E. and Aydogdu, I. (2013), "Review and analysis of swarm-intelligence based algorithms", Swarm Intelligence and Bio-Inspired Computation, Edited by Yang, Cui, Xiao and Gandomi, Elsevier.
  60. Saka, M.P. and Geem, Z.W. (2013), "Mathematical and metaheuristic applications in design optimization of steel frame structures: an extensive review", Math. Prob. Eng., 2013, 1-33.
  61. Shi, Y. and Eberhart, R. (1998). "A modified particle swarm optimizer", Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on.
  62. Tunca, O. and Carbas, S. (2016), "Biogeography-based optimization algorithm for designing of planar steel frames", IJISAE, 4, 53-57.
  63. Ulbrich, K. and Henschel, J. (1999), "Intraspecific competition in a social spider", Ecolog. Model., 115(2), 243-251. https://doi.org/10.1016/S0304-3800(98)00180-X
  64. Vardhini, K.K. and Sitamahalakshmi, T. (2016), "A review on nature-based swarm intelligence optimization techniques and its current research directions", Ind. J. Sci. Technol., 9(10), DOI: 10.17485/ijst/2016/v9i10/81634.
  65. Yang, X.S. (2010), Firefly Algorithm, Levy Flights and Global Optimization, Springer
  66. Yang, X.S., Cui, Z., Xiao, R., Gandomi, A.H. and Karamanoglu, M. (2013), Swarm Intelligence and Bio-inspired Computation: Theory and Applications, Newnes
  67. Yang, X.S. and Deb, S. (2009). "Cuckoo search via Levy flights", Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on.
  68. Yip, E.C., Powers, K.S. and Aviles, L. (2008), "Cooperative capture of large prey solves scaling challenge faced by spider societies", Proceedings of the National Academy of Sciences, 105(33), 11818-11822. https://doi.org/10.1073/pnas.0710603105
  69. Yu, J.J.Q. and Li, V.O.K. (2016), "A social spider algorithm for solving the non-convex economic load dispatch problem", Neurocomput., 171, 955-965. https://doi.org/10.1016/j.neucom.2015.07.037

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