Steel and Composite Structures

  • 제26권2호
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  • Pages.163-170
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  • 2018
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  • 1229-9367(pISSN)
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  • 1598-6233(eISSN)
테크노프레스 (Techno-Press)
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DOI QR코드

DOI QR Code

Jaya algorithm to solve single objective size optimization problem for steel grillage structures

  • Dede, Tayfun (Department of Civil Engineering, Faculty of Engineering, Karadeniz Technical University)
  • 투고 : 2017.08.11
  • 심사 : 2017.11.16
  • 발행 : 2018.01.25
⟨ 이전 논문 다음 논문 ⟩

초록

The purpose of this paper is to present a new and efficient optimization algorithm called Jaya for optimum design of steel grillage structure. Constrained size optimization of this type of structure based on the LRFD-AISC is carried out with integer design variables by using cross-sectional area of W-shapes. The objective function of the problem is to find minimum weight of the grillage structure. The maximum stress ratio and the maximum displacement in the inner point of steel grillage structure are taken as the constraint for this optimization problem. To calculate the moment and shear force of the each member and calculate the joint displacement, the finite elements analysis is used. The developed computer program for the analysis and design of grillage structure and the optimization algorithm for Jaya are coded in MATLAB. The results obtained from this study are compared with the previous works for grillage structure. The results show that the Jaya algorithm presented in this study can be effectively used in the optimal design of grillage structures.

키워드

참고문헌

  1. Artar, M. (2016a), "Optimum design of braced steel frames via teaching learning based optimization", Steel Compos. Struct., Int. J., 22(4), 733-744. https://doi.org/10.12989/scs.2016.22.4.733
  2. Artar, M. (2016b), "A comparative study on optimum design of multi-element truss structures", Steel Compos. Struct., Int. J., 22(3), 521-535. https://doi.org/10.12989/scs.2016.22.3.521
  3. Aydogdu, I., Efe, P., Yetkin, M. and Akin, A. (2017), "Optimum design of steel space structures using social spider optimization algorithm with spider jump technique", Struct. Eng. Mech., Int. J., 62(3), 259-272. https://doi.org/10.12989/sem.2017.62.3.259
  4. Cerny, V. (1985), "Thermodynamical approach to the travelling salesman problem: An efficient simulation algorithm", J. Optim. Theory Appl., 45(1), 41-51. https://doi.org/10.1007/BF00940812
  5. Das, M., Rudrapati, R., Ghosh, N. and Rathod, L. (2016), "Input Parameters optimization in EDM Process using RSM and Jaya Algorithm", Int. J. Current Eng. Technol., 6, 109-112.
  6. Dede, T. (2013), "Optimum design of grillage structures to LRFDAISC with teaching-learning based optimization", Struct. Multidisc. Optim., 48(5), 955-964. https://doi.org/10.1007/s00158-013-0936-3
  7. Dorigo, M. (1991), "Ant Colony Optimization, New Optimization Techniques in Engineering", by Onwubolu, G.C. and Babu, B.V., Springer-Verlag Berlin Heidelberg, pp. 101-117.
  8. Erdal, F. (2007), "Optimum design of grillage system using harmony search algorithm", M.S. Thesis; Middle East Technical University, Ankara, Turkey.
  9. Erdal, F. and Saka, M.P. (2008), "Effect of beam spacing in the harmony search based optimum design of grillages", Asian J. Civil Eng., 9(3), 215-228.
  10. Geem, Z.W., Kim, J.H. and Loganathan, G.V. (2001), "A new heuristic optimization algorithm: harmony search", Simulation, 76(2), 60-68. https://doi.org/10.1177/003754970107600201
  11. Gholizadeh, S., Davoudi, H. and Fattahi, F. (2017), "Design of steel frames by an enhanced moth-flame optimization algorithm", Steel Compos. Struct., Int. J., 24(1), 129-140. https://doi.org/10.12989/scs.2017.24.1.129
  12. Goldberg, D.E. (1989), Genetic Algorithms in Search, Optimization and Machine Learning, New York, USA.
  13. Holland, J.H. (1975), Adaptation in Natural and Artificial Systems, The University of Michigan Press, Ann Arbor, MI, USA.
  14. Kaveh, A. and Abadi, A.S.M. (2011), "Harmony search based algorithms for the optimum cost design of reinforced concrete cantilever retaining walls", Int. J. Civil Eng., 9(1), 1-8.
  15. Kaveh, A. and Mahdavi, V.R. (2015), "Colliding bodies optimization for size and topology optimization of truss structures", Struct. Eng. Mech., Int. J., 53(5), 847-865. https://doi.org/10.12989/sem.2015.53.5.847
  16. Kaveh, A. and Talatahari, S. (2010b), "A novel heuristic optimization method: Charged system search", ActaMechanica, 213(3), 267-289.
  17. Kaveh, A. and Talatahari, S. (2010a), "Charged system search for optimum grillage design using the LRFD-AISC code", J. Construct. Steel Res., 66(6), 767-771. https://doi.org/10.1016/j.jcsr.2010.01.007
  18. Kennedy, J. and Eberhart, R. (1995), "Particle swarm optimization", Proceedings of IEEE International Conference on Neural Networks, Vol. 4 (held in Perth), pp. 1942-1948. Piscataway: IEEE Service Center.
  19. Kirkpatrick, S., Gelatt, C.D. and Vecchi, M.P. (1983), "Optimization by simulated annealing", Science, 220(4598), 671-680. https://doi.org/10.1126/science.220.4598.671
  20. Kurada, R.R. and Kanadam, K.P. (2016), "Automatic Unsupervised Data Classification Using Jaya Evolutionary Algorithm", Adv. Computat. Intel.: Int. J. (ACII), 3(2), 35-42.
  21. LRFD-AISC, Manual of Steel Construction (1999), "Load and resistance factor design. Metric conversion of the second edition", Volume 1-2, AISC, Chicago, IL, USA.
  22. Phulambrikar, S. (2016), "Solving combined economic emission dispatch solution using jaya optimization algorithm approach", Int. Res. J. Eng. Technol. (IRJET), 3(11), 501-512.
  23. Ramanauskas, M., Sesok, D., Belevicius, R., Kurilovas, E. and Valentinavicius, S. (2017), "Genetic algorithm with modified crossover for grillage optimization", Int. J. Comput. Commun. Control, 12(3), 393-401. https://doi.org/10.15837/ijccc.2017.3.2813
  24. Rao, R.V. and Rai, D.P. (2017a), "Optimisation of welding processes using quasi-oppositional-based Jaya algorithm", J. Experim. Theor. Artif. Intel., 29, 1099-1117. https://doi.org/10.1080/0952813X.2017.1309692
  25. Rao, R.V. and Rai, D.P. (2017b), "Optimization of submerged arc welding process parameters using quasi-oppositional based Jaya algorithm", J. Mech. Sci. Technol., 31(5), 2513-2522. https://doi.org/10.1007/s12206-017-0449-x
  26. Rao, R.V., Rai, D.P., Ramkumar, J. and Balic, J. (2016), "A new multi-objective Jaya algorithm for optimization of modern machining processes", Adv. Production Eng. Manage., 11(4), 271-286. https://doi.org/10.14743/apem2016.4.226
  27. Rao, R.V., Rai, D.P. and Balic, J. (2017), "A multi-objective algorithm for optimization of modern machining processes", Eng. Appl. Artif. Intel., 61, 103-125. https://doi.org/10.1016/j.engappai.2017.03.001
  28. Saka, M.P. and Erdal, F. (2009), "Harmony search based algorithm for the optimum design of grillage systems to LRFD-AISC", Struct. Multidiscipl. Optimiz., 38(1), 25-41. https://doi.org/10.1007/s00158-008-0263-2
  29. Saka, M.P., Daloglu, A. and Malhasc, F. (2000), "Optimum spacing design of grillage systems using a genetic algorithm", Adv. Eng. Software, 31(11), 863-873. https://doi.org/10.1016/S0965-9978(00)00048-X
  30. Sesok, D., Belevicius, R. Kaceniauskas, A. and Mockus, J. (2010a), "Application of GRID computing for optimization of grillages", Mechanika, 2(82), 63-69.
  31. Sesok, D., Mockus, J., Belevicius, R. and Kaceniauskas, A. (2010b), "Global optimization of grillages using simulated annealing and high performance computing", J. Civil Eng. Manage., 16(1), 95-101. https://doi.org/10.3846/jcem.2010.09
  32. Topal, U. and O zturk, H.T. (2014),"Buckling load optimization of laminated plates via artificial bee colony algorithm", Struct. Eng. Mech., Int. J., 52(4), 755-765. https://doi.org/10.12989/sem.2014.52.4.755
  33. Warid, W., Hizam, H., Mariun, N. and Abdul-Wahab, N.I. (2016), "Optimal power flow using the jaya algorithm", Energies, 9(678), 1-18.
  34. Zhang, Y., Yang, X., Cattani, C., Rao, R.V., Wang, S. and Phillips, P. (2016), "Tea category identification using a novel fractional fourier entropy and jaya algorithm", Entropy, 18(77), 1-17. https://doi.org/10.3390/e18020001
  35. Zhang, Z., Pan, J., Fu, J., Singh, H.K., Pi, Y.L., Wu, J. and Ra, R. (2017), "Optimization of long span portal frames using spatially distributed surrogates", Steel Compos. Struct., Int. J., 24(2), 227-237.
  36. Zula, T., Kravanja, S. and Klansek, U. (2016), "MINLP optimization of a composite I beam floor system", Steel Compos. Struct., Int. J., 22(5), 1163-1192. https://doi.org/10.12989/scs.2016.22.5.1163

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