Structural Engineering and Mechanics

  • 제47권2호
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  • Pages.209-225
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  • 2013
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  • 1225-4568(pISSN)
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  • 1598-6217(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Design of pin jointed structures using teaching-learning based optimization

  • Togan, Vedat (Karadeniz Technical University, Department of Civil Engineering)
  • 투고 : 2012.06.07
  • 심사 : 2013.07.17
  • 발행 : 2013.07.25
⟨ 이전 논문 다음 논문 ⟩

초록

A procedure employing a Teaching-Learning Based Optimization (TLBO) method is developed to design discrete pin jointed structures. TLBO process consists of two parts: the first part represents learning from teacher and the second part illustrates learning by interaction among the learners. The results are compared with those obtained using other various evolutionary optimization methods considering the best solution, average solution, and computational effort. Consequently, the TLBO algorithm works effectively and demonstrates remarkable performance for the optimization of engineering design applications.

키워드

참고문헌

  1. Camp, C., Pezeshk, S. and Cao, G. (1998), "Optimized design of two dimensional structures using genetic algorithm", J. Struct. Eng., 124(5), 551-559. https://doi.org/10.1061/(ASCE)0733-9445(1998)124:5(551)
  2. Camp, C.V. (2007), "Design of space trusses using big bang?big crunch optimization", J. Struct. Eng., 133(7), 999-1008. https://doi.org/10.1061/(ASCE)0733-9445(2007)133:7(999)
  3. Camp, C.V. and Bichon, B.J. (2004), "Design of space trusses using ant colony optimization", J. Struct. Eng., 130(5), 741-751. https://doi.org/10.1061/(ASCE)0733-9445(2004)130:5(741)
  4. Camp, C.V., Bichon, B.J. and Stovall, S.P. (2005), "Design of steel frames using ant colony optimization", J. Struct. Eng., 131(3), 369-379. https://doi.org/10.1061/(ASCE)0733-9445(2005)131:3(369)
  5. Capriles, P.V.S.Z., Fonseca, L.G., Barbosa, H.J.C. and Lemonge, A.C.C. (2007), "Rank-based ant colony algorithms for truss weight minimization with discrete variables", Commun. Numer. Meth. Eng., 23, 553-575.
  6. Chen, S.Y. and Rajan, S.D. (2000), "A robust genetic algorithm for structural optimization", Struct. Eng. Mech., 10(4), 313-336. https://doi.org/10.12989/sem.2000.10.4.313
  7. Deb, K. (2000), "An efficient constraint handling method for genetic algorithm", Comput. Methods. Appl. Mech. Eng., 186, 311-338. https://doi.org/10.1016/S0045-7825(99)00389-8
  8. Degertekin, S.O. (2007), "Optimum design of steel frames using harmony search algorithm", Struct. Multidisc. Optim., 36, 393-401.
  9. Erbatur, F., Hasancebi, O., Tutuncu, I. and Kılıc, H. (2000), "Optimal design of planar and space structures with genetic algorithms", Comput. Struct., 75, 209-224. https://doi.org/10.1016/S0045-7949(99)00084-X
  10. Karaboga, D. (2005), "An idea based on honey bee swarm for numerical optimization", Technical Report, TR06, Erciyes University, Turkey.
  11. Karaboga, D. and Bagturk, B. (2007), "Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems", Proceeding of LNCS: Advances in Soft Computing: Foundations of Fuzzy Logic and Soft Computing, Cancun, Mexico, June.
  12. Kaveh, A. and Talatahari, S. (2010), "Optimal design of truss structures via the charged system search algorithm", Struct. Multidisc. Optim., 37, 893-911.
  13. Kennedy, J. and Eberhart, R. (1995), "Particle swarm optimization", Proceeding of IEEE International Conference on Neural Networks, Perth, Western Australia, November.
  14. Kripka, M. (2004), "Discrete optimization of trusses by simulated annealing", J. Braz. Soc. Mech. Sci. Eng., XXVI, 170-173.
  15. Lee, K.S. and Geem, Z.W. (2004), "A new structural optimization method based on the harmony search algorithm", Comput. Struct., 82, 781-798. https://doi.org/10.1016/j.compstruc.2004.01.002
  16. Li, L.J., Huang, Z.B. and Liu, F. (2009), "A heuristic particle swarm optimization method for truss structures with discrete variables", Comput. Struct., 87, 435-444. https://doi.org/10.1016/j.compstruc.2009.01.004
  17. Mahfouz, S.Y. (1999), "Design optimization of structural steelwork", Ph.D. thesis, Univ. Of Bradford, Yorkshire.
  18. Nanakorn, P. and Meesomklin, K. (2001), "An adaptive penalty function in genetic algorithms for structural design optimization", Comput. Struct., 79, 2527-2539. https://doi.org/10.1016/S0045-7949(01)00137-7
  19. Rajeev, S. and Krishnamoorthy, C.S. (1992), "Discrete optimization of structures using genetic algorithms", J. Struct. Eng., 118(5), 1233-1250. https://doi.org/10.1061/(ASCE)0733-9445(1992)118:5(1233)
  20. Rao, R.V., Savsani, V.J. and Vakharia, D.P. (2011), "Teaching-learning-based optimization: a novel method for constrained mechanical design optimization problems", Comput-Aided Des., 43, 303-315. https://doi.org/10.1016/j.cad.2010.12.015
  21. Saka, M.P. (2007), "Optimum geometry design of geodesic domes using harmony search algorithm", Adv. Struct. Eng., 10(6), 595-606. https://doi.org/10.1260/136943307783571445
  22. Sonmez, M. (2011), "Discrete optimum design of truss structures using artificial bee colony algorithm", Struct. Multidisc. Optim., 43, 85-97. https://doi.org/10.1007/s00158-010-0551-5
  23. Togan, V. (2011), "Design of planar steel frames using Teaching-Learning Based Optimization", Eng. Struct., 34, 225-232.
  24. Togan, V. and Daloglu, A. (2006), "Optimization of 3d trusses with adaptive approach in genetic algorithms", Eng. Struct., 28, 1019-1027. https://doi.org/10.1016/j.engstruct.2005.11.007
  25. Togan, V. and Daloglu, A. (2006), "Shape and size optimization of 3d trusses with genetic algorithm", Technical J. Turkish Chamber Civil Eng., 17, 3809-3826.
  26. Togan, V. and Daloglu, A. (2008), "An improved genetic algorithm with initial population strategy and self-adaptive member grouping", Comput. Struct., 86, 1204-1218. https://doi.org/10.1016/j.compstruc.2007.11.006
  27. Togan, V. and Daloglu, A. (2009), "Bridge truss optimization under moving load using continuous and discrete design variables in optimization methods", Indian J. Eng. Mater. Sci., 16, 245-258.

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