Steel and Composite Structures

  • 제24권1호
  • /
  • Pages.93-112
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  • 2017
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  • 1229-9367(pISSN)
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  • 1598-6233(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Effect of Levy Flight on the discrete optimum design of steel skeletal structures using metaheuristics

  • Aydogdu, Ibrahim (Department of Civil Engineering, Akdeniz University, Dumlupinar Bvld.) ;
  • Carbas, Serdar (Department of Civil Engineering, Karamanoglu Mehmetbey University) ;
  • Akin, Alper (Trinity Meyer Utility Structures)
  • 투고 : 2016.10.26
  • 심사 : 2017.03.23
  • 발행 : 2017.05.20
⟨ 이전 논문 다음 논문 ⟩

초록

Metaheuristic algorithms in general make use of uniform random numbers in their search for optimum designs. Levy Flight (LF) is a random walk consisting of a series of consecutive random steps. The use of LF instead of uniform random numbers improves the performance of metaheuristic algorithms. In this study, three discrete optimum design algorithms are developed for steel skeletal structures each of which is based on one of the recent metaheuristic algorithms. These are biogeography-based optimization (BBO), brain storm optimization (BSO), and artificial bee colony optimization (ABC) algorithms. The optimum design problem of steel skeletal structures is formulated considering LRFD-AISC code provisions and W-sections for frames members and pipe sections for truss members are selected from available section lists. The minimum weight of steel structures is taken as the objective function. The number of steel skeletal structures is designed by using the algorithms developed and effect of LF is investigated. It is noticed that use of LF results in up to 14% lighter optimum structures.

키워드

참고문헌

  1. Akin, A. and Aydogdu, İ. (2015), "Optimum design of steel space frames by hybrid teaching-learning based optimization and harmony search algorithms", Int. J. Mech. Aerosp. Indust. Mechatron. Manuf. Eng., 9(7), 1367-1374.
  2. Al-Temeemy, A.A., Spencer, J. and Ralph, J. (2010),"Levy flights for improved ladar scanning", Proceedings of 2010 IEEE International Conference on Imaging Systems and Techniques, Thessaloniki, Greece, July.
  3. Artar, M. and Daloglu, A.T. (2015a), "The optimization of multistorey composite steel frames with genetic algorithm including dynamic constraints", Tek Dergi. 26(2), 7077-7098.
  4. Artar, M. and Daloglu, A.T. (2015b), "Optimum design of steel frames with semi-rigid connections and composite beams", Struct. Eng. Mech., Int. J., 55(2), 299-313. https://doi.org/10.12989/sem.2015.55.2.299
  5. Artar, M. and Daloglu, A.T. (2015c), "Optimum design of steel space frames with composite beams using genetic algorithm",, Steel Compos. Struct., Int.J., 19(2), 503-519. https://doi.org/10.12989/scs.2015.19.2.503
  6. ASCE 7-05 (2005), Minimum Design Loads for Buildings and Other Structures, American Society of Civil Engineers, Reston, VA, USA, ABD.
  7. Aydogdu, I. (2010), Optimum Design of 3-D Irregular Steel Frames Using Ant Colony Optimization and Harmony Search Algorithms, Ph.D. Thesis; Middle East Technical University, August, Ankara, Turkey.
  8. Aydogdu, I. (2017), "Cost optimization of reinforced concrete cantilever retaining walls under seismic loading using a biogeography-based optimization algorithm with Levy flights", Eng. Optimiz., 49(3), 381-400. https://doi.org/10.1080/0305215X.2016.1191837
  9. Aydogdu, I. and Akin, A. (2014), "Teaching and learning-based optimization algorithm for optimum design of steel buildings", Comput. Civil Build. Eng., 2167-2175.
  10. Aydogdu, I. and Saka, M.P. (2009), "Ant colony optimization of irregular steel frames including effect of warping", Proceedings of the 12th International Conference on Civil, Structural and Environmental Engineering Computing, Madeira, Portugal, September.
  11. Aydogdu, I., Akin, A. and Saka, M. (2012a), Discrete Design Optimization of Space Steel Frames using the Adaptive Firefly Algorithm, Civil Comp, Dubrovnik, Crotia.
  12. Aydogdu, I., Akin, A. and Saka, M. (2012b), Optimum Design of Steel Space Frames by Artificial Bee Colony Algorithm, Ankara, Turkey.
  13. 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. Software, 92, 1-14. https://doi.org/10.1016/j.advengsoft.2015.10.013
  14. Ben Hadj-Alouane, A. and Bean, J.C. (1997), "A genetic algorithm for the multiple-choice integer program", Operat. Res., 45(1), 92-101. https://doi.org/10.1287/opre.45.1.92
  15. Bhattacharya, A. and Chattopadhyay, P.K. (2010), "Hybrid differential evolution with biogeography-based optimization for solution of economic load dispatch", IEEE Transactions on Power Systems, 25(4), 1955-1964. https://doi.org/10.1109/TPWRS.2010.2043270
  16. Carbas, S. (2016), "Optimum structural design of spatial steel frames via biogeography-based optimization", Neural Comput. Appl., 1-15.
  17. Carbas, S. and Aydogdu, I. (2017), "Utilization of harmony search algorithm in optimal structural design of cold-formed steel structures", Proceedings of International Conference on Harmony Search Algorithm, Bilbao, Spain, February.
  18. Carbas, S., Aydogdu, I. and Saka, M.P. (2009), "Optimum design of steel frames using adaptive harmony search method to LRFD-AISC", Proceedings of the 8th World Congress on Structural and Multidisciplinary Optimization, Lisbon, Portugal, June.
  19. Carbas, S., Aydogdu, I. and Saka, M.P. (2013), "A comparative study of three metaheuristics for optimum design of engineering structures", Proceedings of the 10th World Congress on Structural and Multidisciplinary Optimization, Orlando, FL, USA, May.
  20. Chen, Y. (2010), "Research and simulation on Levy flight model for DTN", Proceedings of the 3rd International Congress on Image and Signal Processing (CISP), Yantai, China, October.
  21. Cheng, S., Qin, Q., Chen, J., Wang, G.-G. and Shi, Y. (2016), "Brain storm optimization in objective space algorithm for multimodal optimization problems", Advances in Swarm Intelligence: Proceedings of the 7th International Conference, ICSI, Bali, Indonesia, June.
  22. Coello, C.A.C. (2002), "Theoretical and numerical constrainthandling techniques used with evolutionary algorithms: A survey of the state of the art", Comput. Method. Appl. Mech. Eng., 191(11), 1245-1287. https://doi.org/10.1016/S0045-7825(01)00323-1
  23. Coello, C.A.C. and Carlos, A. (1999), "A survey of constraint handling techniques used with evolutionary algorithms", Lania-RI-99-04, Laboratorio Nacional de Informatica Avanzada.
  24. Degertekin, S. (2012), "Optimum design of geometrically nonlinear steel frames using artificial bee colony algorithm", Steel Compos. Struct., Int. J., 12(6), 505-522. https://doi.org/10.12989/scs.2012.12.6.505
  25. Digalakis, J.G. and Margaritis, K.G. (2002), "An experimental study of benchmarking functions for genetic algorithms", Int. J. Comput. Math., 79(4), 403-416. https://doi.org/10.1080/00207160210939
  26. Dorigo, M. (1992), Optimization, Learning and Natural Algorithms, Politecnicodi Milano, Milano, Italy.
  27. Eberhart, R.C. and Kennedy, J. (1995), "A new optimizer using particle swarm theory", Proceedings of the 6th International Symposium on Micro Machine and Human Science, Nagoya, Japan, October.
  28. 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)
  29. Fourie, P. and Groenwold, A.A. (2002), "The particle swarm optimization algorithm in size and shape optimization", Struct. Multidiscipl. Optimiz., 23(4), 259-267. https://doi.org/10.1007/s00158-002-0188-0
  30. Gandomi, A.H. and Yang, X.-S. (2014), "Chaotic bat algorithm", J. Computat. Sci., 5(2), 224-232. https://doi.org/10.1016/j.jocs.2013.10.002
  31. Geem, Z.W., Kim, J.H. and Loganathan, G. (2001), "A new heuristic optimization algorithm: harmony search", Simulation, 76(2), 60-68. https://doi.org/10.1177/003754970107600201
  32. Gong, W., Cai, Z., Ling, C.X. and Li, H. (2010), "A real-coded biogeography-based optimization with mutation", Appl. Math. Computat., 216(9), 2749-2758. https://doi.org/10.1016/j.amc.2010.03.123
  33. Hadidi, A., Azad, S.K. and Azad, S.K. (2010), "Structural optimization using artificial bee colony algorithm", Proceedings of the 2nd International Conference on Engineering Optimization, Lisbon, Portugal, September.
  34. Hasancebi, O. and Azad, S.K. (2014), "Discrete size optimization of steel trusses using a refined big bang-big crunch algorithm", Eng. Optimiz., 46(1), 61-83. https://doi.org/10.1080/0305215X.2012.748047
  35. Hasancebi, O. and Carbas, S. (2011), "Ant colony search method in practical structural optimization", Int. J. Optimiz. Civil Eng., 1(1), 91-105.
  36. Homaifar, A., Qi, C.X. and Lai, S.H. (1994), "Constrained optimization via genetic algorithms", Simulation, 62(4), 242-253. https://doi.org/10.1177/003754979406200405
  37. Jalili, S., Hosseinzadeh, Y. and Kaveh, A. (2014), "Chaotic biogeography algorithm for size and shape optimization of truss structures with frequency constraints", Periodica Polytechnica. Civil Engineering, 58(4), 397. https://doi.org/10.3311/PPci.7466
  38. Joines, J.A. and Houck, C.R. (1994), "On the use of non-stationary penalty functions to solve nonlinear constrained optimization problems with GA's", Proceedings of the 1st IEEE Conference on Evolutionary Computation IEEE World Congress on Computational Intelligence, New York, NY, USA, June.
  39. Jordehi, A.R. (2014), "A chaotic-based big bang-big crunch algorithm for solving global optimisation problems", Neural Comput. Appl., 25(6), 1329-1335. https://doi.org/10.1007/s00521-014-1613-1
  40. Jordehi, A.R. (2015a), "Brainstorm optimisation algorithm (BSOA): An efficient algorithm for finding optimal location and setting of FACTS devices in electric power systems", Int. J. Electric. Power Energy Syst., 69, 48-57. https://doi.org/10.1016/j.ijepes.2014.12.083
  41. Jordehi, A.R. (2015b), "A chaotic artificial immune system optimisation algorithm for solving global continuous optimisation problems", Neural Comput. Appl., 26(4), 827-833. https://doi.org/10.1007/s00521-014-1751-5
  42. Jordehi, A.R. (2015c), "Chaotic bat swarm optimisation (CBSO)", Appl. Soft Comput., 26, 523-530. https://doi.org/10.1016/j.asoc.2014.10.010
  43. Jordehi, A.R. (2015d), "Enhanced leader PSO (ELPSO): A new PSO variant for solving global optimisation problems", Appl. Soft Comput., 26, 401-417. https://doi.org/10.1016/j.asoc.2014.10.026
  44. Jordehi, A.R. (2015e), "A review on constraint handling strategies in particle swarm optimisation", Neural Comput. Appl., 26(6), 1265-1275. https://doi.org/10.1007/s00521-014-1808-5
  45. Karaboga, D. (2005), An Idea Based on Honey Bee Swarm for Numerical Optimization, Technical Report-tr06; Erciyes University, Engineering Faculty, Computer Engineering Department.
  46. Karaboga, D. and Basturk, B. (2007), "A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm", J. Global Optimiz., 39(3), 459-471. https://doi.org/10.1007/s10898-007-9149-x
  47. Karaboga, D. and Basturk, B. (2008), "On the performance of artificial bee colony (ABC) algorithm", Appl. Soft Comput., 8(1), 687-697. https://doi.org/10.1016/j.asoc.2007.05.007
  48. Kaveh, A., Sheikholeslami, R., Talatahari, S. and Keshvari-Ilkhichi, M. (2014), "Chaotic swarming of particles: a new method for size optimization of truss structures", Adv. Eng. Softw., 67, 136-147. https://doi.org/10.1016/j.advengsoft.2013.09.006
  49. Lee, K.S. and Geem, Z.W. (2004), "A new structural optimization method based on the harmony search algorithm", Comput. Struct., 82(9), 781-798. https://doi.org/10.1016/j.compstruc.2004.01.002
  50. Lenin, K., Ravindhranath Reddy, B. and Surya Kalavathi, M. (2014), "Brain storm optimization algorithm for solving optimal reactive power dispatch problem", Int. J. Res. Electron. Commun. Technol., 1(3).
  51. Levy, P. (1939), "L'addition des variables aleatoires definies sur une circonference", Bulletin de la Societe Mathematique de France, 67, 1-41.
  52. Li, J.N. and Duan, H.B. (2015), "Simplified brain storm optimization approach to control parameter optimization in F/A-18 automatic carrier landing system", Aerosp. Sci. Technol., 42, 187-195. https://doi.org/10.1016/j.ast.2015.01.017
  53. LRFD (2000), Load & Resistance Factor Design Specification; American Institute of Steel Construction, Chicago, IL, USA.
  54. Michalewicz, Z. and Nazhiyath, G. (1995), "Genocop III: A coevolutionary algorithm for numerical optimization problems with nonlinear constraints", Proceedings of IEEE International Conference on Evolutionary Computation, Perth, Australia, November-December.
  55. Pereyra, M.A. and Batatia, H. (2010), "A Levy flight model for ultrasound in skin tissues", Proceedings of 2010 IEEE International Ultrasonics Symposium, San Diego, CA, USA, October.
  56. Perez, R. and Behdinan, K. (2007), "Particle swarm approach for structural design optimization", Comput. Struct., 85(19), 1579-1588. https://doi.org/10.1016/j.compstruc.2006.10.013
  57. Rashedi, E., Nezamabadi-Pour, H. and Saryazdi, S. (2009), "GSA: A gravitational search algorithm", Inform. Sci., 179(13), 2232-2248. https://doi.org/10.1016/j.ins.2009.03.004
  58. Roy, P.K., Ghoshal, S.P. and Thakur, S.S. (2011), "Optimal reactive power dispatch considering flexible AC transmission system devices using biogeography-based optimization", Electric Power Components Syst., 39(8), 733-750. https://doi.org/10.1080/15325008.2010.541410
  59. Saka, M.P., Aydogdu, I. and Hasancebi, O. (2010), "Evaluation of recent improvements in harmony search based structural optimization algorithms", Proceedings of the 10th International Conference on Computational Structures Technology, Valencia, Spain, September.
  60. Saka, M.P., Aydogdu, I., Hasancebi, O. and Geem, Z.W. (2011), Harmony Search Algorithms in Structural Engineering, Springer.
  61. Saka, M., Carbas, S., Aydogdu, I., Akin, A. and Geem, Z. (2015), Comparative Study on Recent Metaheuristic Algorithms in Design Optimization of Cold-Formed Steel Structures, Springer, Cham, Switzerland.
  62. Salcedo-Sanz, S. (2009), "A survey of repair methods used as constraint handling techniques in evolutionary algorithms", Comput. Sci. Review, 3(3), 175-192. https://doi.org/10.1016/j.cosrev.2009.07.001
  63. Shi, Y. (2011), Brain Storm Optimization Algorithm, Springer.
  64. Shi, Y. (2014), "An optimization algorithm based on brainstorming process", Emerg. Res. Swarm Intel. Algorithm Optimiz., 1.
  65. Shi, Y. and Eberhart, R. (1998), "A modified particle swarm optimizer", Proceedings of the 1998 IEEE World Congress on Computational Intelligence; IEEE International Conference on Evolutionary Computation, Anchorage, AK, USA, May.
  66. Simon, D. (2008), "Biogeography-based optimization", IEEE Transact. Evolution. Computat., 12(6), 702-713. https://doi.org/10.1109/TEVC.2008.919004
  67. Sonmez, M. (2011), "Discrete optimum design of truss structures using artificial bee colony algorithm", Struct. Multidiscipl. Optimiz., 43(1), 85-97. https://doi.org/10.1007/s00158-010-0551-5
  68. Surry, P.D., Radcliffe, N.J. and Boyd, I.D. (1995), "A multiobjective approach to constrained optimisation of gas supply networks: The COMOGA Method", AISB Workshop on Evolutionary Computing.
  69. Talatahari, S., Kaveh, A. and Sheikholeslami, R. (2012), "Chaotic imperialist competitive algorithm for optimum design of truss structures", Struct. Multidiscipl. Optimiz., 46(3), 355-367. https://doi.org/10.1007/s00158-011-0754-4
  70. Terdik, G. and Gyires, T. (2009), "Levy flights and fractal modeling of internet traffic", IEEE/ACM Transactions on Networking, 17(1), 120-129. https://doi.org/10.1109/TNET.2008.925630
  71. Wang, J.S., Shen, N.N., Ren, X.D. and Liu, G.N. (2015), "RBF neural network soft-sensor modeling of Rotary Kiln Pellet quality indices optimized by biogeography-based optimization algorithm", J. Chem. Eng. Jpn, 48(1), 7-15. https://doi.org/10.1252/jcej.14we135
  72. Yang, X.-S. (2010), Nature-Inspired Metaheuristic Algorithms, Luniver Press.
  73. Yang, X.-S., Bekdas, G. and Nigdeli, S.M. (2016), Review and Applications of Metaheuristic Algorithms in Civil Engineering, Springer
  74. Yang, G.-P., Liu, S.-Y., Zhang, J.-K. and Feng, Q.-X. (2013), "Control and synchronization of chaotic systems by an improved biogeography-based optimization algorithm", Appl. Intel., 39(1), 132-143. https://doi.org/10.1007/s10489-012-0398-0
  75. Yang, X.-S. and Deb, S. (2009), "Cuckoo search via Levy flights", Proceedings of World Congress on Nature & Biologically Inspired Computing; NaBIC, Coimbatore, India, December.
  76. Yetkin, M. (2015), Duzlem celik cercevelerin sosyal orumcek optimizasyonuna gore boyutlandirilmasi (Optimum design of plane steel frames according to social spider optimization), Balikesir University, YOK Tez Merkezi, Turkey.
  77. Zhan, Z.-h., Chen, W.-n., Lin, Y., Gong, Y.-j., Li, Y.-l. and Zhang, J. (2013), "Parameter investigation in brain storm optimization", Proceedings of 2013 IEEE Symposium on Swarm Intelligence (SIS), Singapore, April.

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