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Harmony Search Algorithm for Structural Engineering Problems

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Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications

Part of the book series: Springer Tracts in Nature-Inspired Computing ((STNIC))

Abstract

Nowadays, several new metaheuristic methods have been developed by imitating a process in life. These algorithms may be practically effective on optimization of engineering problem, and these algorithms may disappear in time. Despite that, classical and frequently proved algorithm by the success of optimization will live forever, and these algorithms are modified up to date to provide the needs of the future. The harmony search (HS) algorithm is one of these algorithms, and the initial born of this algorithm was provided by the observation of musical performances. By the start of development of HS, several optimization methodologies have been developed for structural engineering problems. In this chapter, a state-of-the-art study is presented for structural optimization problems employing HS or variants of it. It is possible to find the modification period HS on structural engineering problems. The process of several variants is also briefly explained for a structural engineering benchmark problem with computer codes, and the performance of different variants is compared.

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References

  1. Schmit LA (1960) Structural design by systematic synthesis. In: Proceedings of the second national conference on electronic computation, ASCE, Sept 1960

    Google Scholar 

  2. Saka MP, Hasançebi O, Geem ZW (2016) Metaheuristics in structural optimization and discussions on harmony search algorithm. Swarm Evol Comput 28:88–97

    Article  Google Scholar 

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

    Google Scholar 

  4. Arora JS, Wang Q (2005) Review of formulations for structural and mechanical system optimization. Struct Multidiscipl Optim 30(4):251–272

    Article  MathSciNet  MATH  Google Scholar 

  5. Saka MP (2003) Optimum design of skeletal structures: a review. Prog Civil Struct Eng Comput 10:237–284

    Article  Google Scholar 

  6. Saka MP (2007) Optimum design of steel frames using stochastic search techniques based on natural phenomena: a review. Civil engineering computations: tools and techniques. Saxe-Coburg Publications, Stirlingshire, UK, pp 105–147

    Google Scholar 

  7. Saka MP (2007) Optimization in structural engineering. In: Geem ZW (ed) Optimization in civil & environmental engineering. Old City Publishing, Philadelphia, pp 59–123

    Google Scholar 

  8. Saka MP, Geem ZW (2013) Mathematical and metaheuristic applications in design optimization of steel frame structures: an extensive review. Math Probl Eng. Article ID 271031

    Google Scholar 

  9. Venter G (2010) Review of optimization techniques. In: Blockley R, Shyy W (eds) Encyclopedia of aerospace engineering. Wiley, Hoboken, NJ

    Google Scholar 

  10. Geem ZW, Kim JH, Loganathan GV (2001) A new heuristic optimization algorithm: harmony search. Simulation 76:60–68

    Article  Google Scholar 

  11. Koziel S, Yang XS (2011) Computational optimization, methods and algorithms, vol 356. Springer, Heidelberg, Berlin. ISBN: 978-3-642-20858-4

    Google Scholar 

  12. Onwubolu GC, Babu BV (2004) New optimization techniques in engineering, vol 141. Springer, Heidelberg, Berlin. ISBN: 978-3-540-39930-8

    Google Scholar 

  13. Gandomi AH, Yang XS, Talatahari S, Alavi AH (2013) Metaheuristic algorithms in modeling and optimization. Metaheuristic applications in structures and infrastructures. Elsevier, pp 1–24. ISBN: 9780123983640

    Google Scholar 

  14. Yang XS, Koziel S, Leifsson L (2013) Computational optimization, modelling and simulation: recent trends and challenges. In: International conference on computational science, ICCS 2013, 5–7 Haziran 2013 Barselona-İspanya. Procedia Computer Science, pp 855–860

    Google Scholar 

  15. Erdoğmuş P (2016) Doğadan esinlenen optimizasyon algoritmaları ve optimizasyon algoritmalarının optimizasyonu. Düzce Üniversitesi Bilim ve Teknoloji Dergisi 4(1):293–304

    MathSciNet  Google Scholar 

  16. Onan A (2013) Metasezgisel yöntemler ve uygulama alanları. Çukurova Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 17(2):113–128

    Google Scholar 

  17. Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor, MI

    Google Scholar 

  18. Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220(4598):671–680

    Article  MathSciNet  MATH  Google Scholar 

  19. Glover F (1986) Future paths for integer programming and links to artificial intelligence. Comput Oper Res 13(5):533–549

    Article  MathSciNet  MATH  Google Scholar 

  20. Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Proceedings of IEEE international conference on neural networks, no IV, 27 Nov–1 Dec, Perth Australia, pp 1942–1948

    Google Scholar 

  21. Dorigo M, Maniezzo V, Colorni A (1996) The ant system: optimization by a colony of cooperating agents. IEEE Trans Syst Man Cybern B 26:29–41

    Article  Google Scholar 

  22. Storn R, Price K (1997) Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces. J Global Optim 11(4):341–359

    Article  MathSciNet  MATH  Google Scholar 

  23. Erol OK, Eksin I (2006) A new optimization method: big bang–big crunch. Adv Eng Softw 37(2):106–111

    Article  Google Scholar 

  24. Karaboga D, Basturk B (2007) A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J Global Optim 39(3):459–471

    Article  MathSciNet  MATH  Google Scholar 

  25. Yang XS, Deb S (2010) Engineering optimisation by cuckoo search. Int J Math Model Numer Optim 1(4):330–343

    MATH  Google Scholar 

  26. Yang XS (2010) Firefly algorithm, stochastic test functions and design optimisation. Int J Bio-Inspir Comput 2(2):78–84

    Article  Google Scholar 

  27. Yang XS (2010) A new metaheuristic bat-inspired algorithm. In: Nature inspired cooperative strategies for optimization (NICSO 2010). Springer, Berlin, Heidelberg, pp 65–74

    Google Scholar 

  28. Rao RV, Savsani VJ, Vakharia DP (2011) Teaching–learning-based optimization: a novel method for constrained mechanical design optimization problems. Comput Aided Des 43(3):303–315

    Article  Google Scholar 

  29. Yang XS (2012) Flower pollination algorithm for global optimization. In: International conference on unconventional computing and natural computation. Springer, Berlin, Heidelberg, pp 240–249

    Google Scholar 

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

    Article  Google Scholar 

  31. Gandomi AH, Alavi AH (2012) Krill herd: a new bio-inspired optimization algorithm. Commun Nonlinear Sci Numer Simul 17(12):4831–4845

    Article  MathSciNet  MATH  Google Scholar 

  32. Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46–61

    Article  Google Scholar 

  33. Rao R (2016) Jaya: a simple and new optimization algorithm for solving constrained and unconstrained optimization problems. Int J Ind Eng Comput 7(1):19–34

    Google Scholar 

  34. Kaveh A, Khanzadi M, Moghaddam MR (2020) Billiards-inspired optimization algorithm; a new meta-heuristic method. In: Structures, vol 27. Elsevier, pp 1722–1739

    Google Scholar 

  35. Mahdavi M, Fesanghary M, Damangir E (2007) An improved harmony search algorithm for solving optimization problems. Appl Math Comput 188(2):1567–1579

    MathSciNet  MATH  Google Scholar 

  36. Kumar V, Chhabra JK, Kumar D (2016) Automatic data clustering using parameter adaptive harmony search algorithm and its application to image segmentation. J Intell Syst 25(4):595–610

    Article  Google Scholar 

  37. dos Santos Coelho L, de Andrade Bernert DL (2009) An improved harmony search algorithm for synchronization of discrete-time chaotic systems. Chaos Solitons Fractals 41(5):2526–2532

    Article  MATH  Google Scholar 

  38. Hasançebi O, Erdal F, Saka MP (2010) Adaptive harmony search method for structural optimization. J Struct Eng 136(4):419–431

    Article  Google Scholar 

  39. Papa JP, Scheirer W, Cox DD (2016) Fine-tuning deep belief networks using harmony search. Appl Soft Comput 46:875–885

    Article  Google Scholar 

  40. Choi YH, Lee HM, Yoo DG, Kim JH (2017) Self-adaptive multi-objective harmony search for optimal design of water distribution networks. Eng Optim 49(11):1957–1977

    Article  MathSciNet  Google Scholar 

  41. Geem ZW, Sim KB (2010) Parameter-setting-free harmony search algorithm. Appl Math Comput 217(8):3881–3889

    MathSciNet  MATH  Google Scholar 

  42. Jeong YW, Park SM, Geem ZW, Sim KB (2020) Advanced parameter-setting-free harmony search algorithm. Appl Sci 10(7):2586

    Article  Google Scholar 

  43. Tuo S, Zhang J, Yuan X, Zhang Y, Liu Z (2016) FHSA-SED: two-locus model detection for genome-wide association study with harmony search algorithm. PLoS ONE 11(3):e0150669

    Article  Google Scholar 

  44. Wang G, Guo L (2013) A novel hybrid bat algorithm with harmony search for global numerical optimization. J Appl Math 2013

    Google Scholar 

  45. Pandi VR, Panigrahi BK (2011) Dynamic economic load dispatch using hybrid swarm intelligence based harmony search algorithm. Expert Syst Appl 38(7):8509–8514

    Article  Google Scholar 

  46. Wu B, Qian C, Ni W, Fan S (2012) Hybrid harmony search and artificial bee colony algorithm for global optimization problems. Comput Math Appl 64(8):2621–2634

    Article  MathSciNet  MATH  Google Scholar 

  47. Abdel-Raouf O, El-Henawy I, Abdel-Baset M (2014) A novel hybrid flower pollination algorithm with chaotic harmony search for solving Sudoku puzzles. Int J Mod Educ Comput Sci 6(3):38

    Article  Google Scholar 

  48. Assad A, Deep K (2018) A hybrid harmony search and simulated annealing algorithm for continuous optimization. Inf Sci 450:246–266

    Article  Google Scholar 

  49. Kaveh A, Talatahari S (2009) Hybrid algorithm of harmony search, particle swarm and ant colony for structural design optimization. In: Harmony search algorithms for structural design optimization. Springer, Berlin, Heidelberg, pp 159–198

    Google Scholar 

  50. Gheisarnejad M (2018) An effective hybrid harmony search and cuckoo optimization algorithm based fuzzy PID controller for load frequency control. Appl Soft Comput 65:121–138

    Article  Google Scholar 

  51. Feng Y, Wang GG, Gao XZ (2016) A novel hybrid cuckoo search algorithm with global harmony search for 0-1 knapsack problems. Int J Comput Intell Syst 9(6):1174–1190

    Article  Google Scholar 

  52. Guo L, Wang GG, Wang H, Wang D (2013) An effective hybrid firefly algorithm with harmony search for global numerical optimization. Sci World J 2013

    Google Scholar 

  53. Manjarres D, Landa-Torres I, Gil-Lopez S, Del Ser J, Bilbao MN, Salcedo-Sanz S, Geem ZW (2013) A survey on applications of the harmony search algorithm. Eng Appl Artif Intell 26(8):1818–1831

    Article  Google Scholar 

  54. Yang XS, Bekdaş G, Nigdeli SM (2016) Review and applications of metaheuristic algorithms in civil engineering. In: Metaheuristics and optimization in civil engineering. Springer, Cham, pp 1–24

    Google Scholar 

  55. Nasir M, Sadollah A, Yoon JH, Geem ZW (2020) Comparative study of harmony search algorithm and its applications in China, Japan and Korea. Appl Sci 10(11):3970

    Article  Google Scholar 

  56. Ala’a A, Alsewari AA, Alamri HS, Zamli KZ (2019) Comprehensive review of the development of the harmony search algorithm and its applications. IEEE Access 7:14233–14245

    Google Scholar 

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

    Article  Google Scholar 

  58. Lee KS, Geem ZW, Lee SH, Bae KW (2005) The harmony search heuristic algorithm for discrete structural optimization. Eng Optim 37(7):663–684

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  60. Sadollah A, Sayyaadi H, Lee HM, Kim JH (2018) Mine blast harmony search: a new hybrid optimization method for improving exploration and exploitation capabilities. Appl Soft Comput 68:548–564

    Article  Google Scholar 

  61. Sadollah A, Bahreininejad A, Eskandar H, Hamdi M (2012) Mine blast algorithm for optimization of truss structures with discrete variables. Comput Struct 102:49–63

    Article  Google Scholar 

  62. Cheng MY, Prayogo D, Wu YW, Lukito MM (2016) A Hybrid Harmony Search algorithm for discrete sizing optimization of truss structure. Autom Constr 69:21–33

    Article  Google Scholar 

  63. Cao H, Qian X, Zhou YL, Yang H (2018) Applicability of subspace harmony search hybrid with improved deb rule in optimizing trusses. J Comput Civil Eng 32(4):04018021

    Article  Google Scholar 

  64. Saka MP (2009) Optimum design of steel skeleton structures. In: Music-inspired harmony search algorithm. Springer, Berlin, Heidelberg, pp 87–112

    Google Scholar 

  65. Saka MP (2009) Optimum design of steel sway frames to BS5950 using harmony search algorithm. J Constr Steel Res 65(1):36–43

    Article  MathSciNet  Google Scholar 

  66. AISC A (1989) Manual of steel construction–allowable stress design. American Institute of Steel Construction (AISC), Chicago

    Google Scholar 

  67. Artar M, Daloğlu AT (2018) Optimum weight design of steel space frames with semi-rigid connections using harmony search and genetic algorithms. Neural Comput Appl 29(11):1089–1100

    Article  Google Scholar 

  68. MATLAB (2009) The language of technical computing. The Mathworks, Natick

    Google Scholar 

  69. SAP2000 (2008) Integrated finite elements analysis and design of structures. Computers and Structures Inc, Berkeley

    Google Scholar 

  70. Arafa M, Khalifa A, Alqedra M (2016) Design optimization of semi-rigidly connected steel frames using harmony search algorithm. J Eng Res Technol 2(2)

    Google Scholar 

  71. Carbas S, Saka MP (2009) Optimum design of single layer network domes using harmony search method. Asian J Civil Eng 10(1):97–112

    Google Scholar 

  72. Çarbaş S, Saka MP (2012) Optimum topology design of various geometrically nonlinear latticed domes using improved harmony search method. Struct Multidiscipl Optim 45(3):377–399

    Article  Google Scholar 

  73. Carbas S, Aydogdu I (2017) Utilization of harmony search algorithm in optimal structural design of cold-formed steel structures. In: Del Ser J (ed) Harmony search algorithm. ICHSA 2017. Advances in intelligent systems and computing, vol 514. Springer, Singapore

    Google Scholar 

  74. Erdal F, Doğan E, Saka MP (2011) Optimum design of cellular beams using harmony search and particle swarm optimizers. J Constr Steel Res 67(2):237–247

    Article  Google Scholar 

  75. Kayabekir AE, Bekdaş G, Nigdeli SM (eds) (2020) Metaheuristic approaches for optimum design of reinforced concrete structures: emerging research and opportunities: emerging research and opportunities. IGI Global

    Google Scholar 

  76. Akin A, Saka MP (2010) Optimum detailed design of reinforced concrete continuous beams using the harmony search algorithm. In: The tenth international conference on computational structures technology, Paper 131, Stirlingshire, UK

    Google Scholar 

  77. ACI-318 (2005) Building code requirements for structural concrete and commentary, metric version. American Concrete Institute

    Google Scholar 

  78. Jaberipour M, Khorram E (2011) A new harmony search algorithm for solving mixed–discrete engineering optimization problems. Eng Optim 43(5):507–523

    Article  Google Scholar 

  79. Bekdaş G, Nigdeli SM (2013) Optimization of T-shaped RC flexural members for different compressive strengths of concrete. Int J Mech 7:109–119

    Google Scholar 

  80. Shaqfa M, Orbán Z (2019) Modified parameter-setting-free harmony search (PSFHS) algorithm for optimizing the design of reinforced concrete beams. Struct Multidiscipl Optim 60(3):999–1019

    Article  Google Scholar 

  81. de Medeiros GF, Kripka M (2012) Harmony search algorithm applied to the optimization of reinforced concrete columns

    Google Scholar 

  82. Bekdas G, Nigdeli SM (2014) The optimization of slender reinforced concrete columns. Proc Appl Math Mech 14(1):183–184

    Article  Google Scholar 

  83. Nigdeli SM, Bekdas G, Kim S, Geem ZW (2015) A novel harmony search based optimization of reinforced concrete biaxially loaded columns. Struct Eng Mech 54(6):1097–1109

    Article  Google Scholar 

  84. Medeiros GF, Kripka M (2017) Modified harmony search and its application to cost minimization of RC columns. Adv Comput Des 2(1):1–13

    Google Scholar 

  85. Nigdeli SM, Bekdaş G (2014) Optimization of reinforced concrete shear walls using harmony search. In: 11th international congress on advances in civil engineering, Istanbul, Turkey. Academic

    Google Scholar 

  86. Akin A, Saka MP (2015) Harmony search algorithm based optimum detailed design of reinforced concrete plane frames subject to ACI 318-05 provisions. Comput Struct 147:79–95

    Article  Google Scholar 

  87. Bekdaş G, Nigdeli SM (2017) Modified harmony search for optimization of reinforced concrete frames. In: 3rd international conference on the harmony search algorithm (ICHSA 2017), Bilbao, Spain

    Google Scholar 

  88. Boscardin JT, Yepes V, Kripka M (2019) Optimization of reinforced concrete building frames with automated grouping of columns. Autom Constr 104:331–340

    Article  Google Scholar 

  89. Bekdas G (2014) Optimum design of axially symmetric cylindrical reinforced concrete walls. Struct Eng Mech 51(3):361–375. https://doi.org/10.12989/sem.2014.51.3.361

    Article  Google Scholar 

  90. Bekdaş G (2015) Harmony search algorithm approach for optimum design of post-tensioned axially symmetric cylindrical reinforced concrete walls. J Optim Theory Appl 164(1):342–358

    Article  MathSciNet  MATH  Google Scholar 

  91. Bekdaş G, Nigdeli SM (2018) Optimum reduction of flexural effect of axially symmetric cylindrical walls with post-tensioning forces. KSCE J Civil Eng 1–8

    Google Scholar 

  92. Bekdaş G (2018) New improved metaheuristic approaches for optimum design of posttensioned axially symmetric cylindrical reinforced concrete walls. Struct Des Tall Spec Build 27(7)

    Google Scholar 

  93. Molina-Moreno F, García-Segura T, Martí JV, Yepes V (2017) Optimization of buttressed earth-retaining walls using hybrid harmony search algorithms. Eng Struct 134:205–216

    Article  Google Scholar 

  94. Manahiloh KN, Nejad MM, Momeni MS (2015) Optimization of design parameters and cost of geosynthetic-reinforced earth walls using harmony search algorithm. Int J Geosynth Ground Eng 1(2):15

    Article  Google Scholar 

  95. Bekdaş G, Nigdeli SM (2015) Multi-objective optimization of reinforced concrete footings using harmony search. In: 23rd international conference on multiple criteria decision making (MCDM 2015), Hamburg, Germany. Academic

    Google Scholar 

  96. Bekdaş G, Arama ZA, Kayabekir AE, Geem ZW (2020) Optimal design of cantilever soldier pile retaining walls embedded in frictional soils with harmony search algorithm. Appl Sci 10(9):3232

    Article  Google Scholar 

  97. Arama ZA, Kayabekir AE, Bekdaş G, Geem ZW (2020) CO2 and cost optimization of reinforced concrete cantilever soldier piles: a parametric study with harmony search algorithm. Sustainability 12(15):5906

    Article  Google Scholar 

  98. Kayabekir AE, Arama ZA, Bekdaş G, Nigdeli SM, Geem ZW (2020) Eco-friendly design of reinforced concrete retaining walls: multi-objective optimization with harmony search applications. Sustainability 12(15):6087

    Article  Google Scholar 

  99. Aydogdu I, Akin A (2015) Biogeography based CO2 and cost optimization of RC cantilever retaining walls. In: 17th international conference on structural engineering, pp 1480–1485

    Google Scholar 

  100. Toklu YC, Bekdaş G, Geem ZW (2020) Harmony search optimization of nozzle movement for additive manufacturing of concrete structures and concrete elements. Appl Sci 10(12):4413

    Article  Google Scholar 

  101. García-Segura T, Yepes V, Alcalá J, Pérez-López E (2015) Hybrid harmony search for sustainable design of post-tensioned concrete box-girder pedestrian bridges. Eng Struct 92:112–122

    Article  Google Scholar 

  102. Bekdaş G, Nigdeli SM (2011) Estimating optimum parameters of tuned mass dampers using harmony search. Eng Struct 33(9):2716–2723

    Article  Google Scholar 

  103. Bekdaş G, Nigdeli SM (2013) Mass ratio factor for optimum tuned mass damper strategies. Int J Mech Sci 71:68–84

    Article  Google Scholar 

  104. Nigdeli SM, Bekdas G (2013) Optimum tuned mass damper design for preventing brittle fracture of RC buildings. Smart Struct Syst 12(2):137–155

    Article  Google Scholar 

  105. Nigdeli SM, Bekdaş G (2014) Optimization of TMDs for different objectives. In: An international conference on engineering and applied sciences optimization, Kos Island, Greece, pp 4–6

    Google Scholar 

  106. Bekdaş G, Nigdeli SM (2012) Preventing the pounding of adjacent buildings with harmony search optimized tuned mass damper. In: 3rd European conference of civil engineering, pp 2–4

    Google Scholar 

  107. Nigdeli SM, Bekdas G (2013) The effect of impulsive motions on optimum tuned mass damper parameters. In: 11th international conference on vibration problems, pp 2–10

    Google Scholar 

  108. Nigdeli SM, Bekdas G (2014) Optimum tuned mass damper approaches for adjacent structures. Earthq Struct 7(6):1071–1091

    Article  Google Scholar 

  109. Nigdeli SM, Bekdaş G (2017) Optimum tuned mass damper design in frequency domain for structures. KSCE J Civil Eng 21(3):912–922

    Article  Google Scholar 

  110. Bekdaş G, Nigdeli SM (2017) Metaheuristic based optimization of tuned mass dampers under earthquake excitation by considering soil-structure interaction. Soil Dyn Earthq Eng 92:443–461

    Article  Google Scholar 

  111. Nigdeli SM, Bekdaş G, Yang XS (2017). Optimum tuning of mass dampers by using a hybrid method using harmony search and flower pollination algorithm. In: International conference on harmony search algorithm, February. Springer, Singapore, pp 222–231

    Google Scholar 

  112. Zhang HY, Zhang LJ (2017) Tuned mass damper system of high-rise intake towers optimized by improved harmony search algorithm. Eng Struct 138:270–282

    Article  Google Scholar 

  113. Keshtegar B, Etedali S (2018) Nonlinear mathematical modeling and optimum design of tuned mass dampers using adaptive dynamic harmony search algorithm. Struct Control Health Monit 25(7):e2163

    Article  Google Scholar 

  114. Bekdaş G, Kayabekir AE, Nigdeli SM, Toklu YC (2019) Tranfer function amplitude minimization for structures with tuned mass dampers considering soil-structure interaction. Soil Dyn Earthq Eng 116:552–562

    Article  Google Scholar 

  115. Amini F, Ghaderi P (2013) Hybridization of harmony search and ant colony optimization for optimal locating of structural dampers. Appl Soft Comput 13(5):2272–2280

    Article  Google Scholar 

  116. Nigdeli SM, Bekdaş G, Alhan C (2014) Optimization of seismic isolation systems via harmony search. Eng Optim 46(11):1553–1569

    Article  Google Scholar 

  117. Kayabekir AE, Bekdaş G, Nigdeli SM, Geem ZW (2020) Optimum design of PID controlled active tuned mass damper via modified harmony search. Appl Sci 10(8):2976

    Article  Google Scholar 

  118. de Almeida FS (2019) Optimization of laminated composite structures using harmony search algorithm. Compos Struct 221:110852

    Article  Google Scholar 

  119. Kaveh A, Abadi ASM (2010) Cost optimization of a composite floor system using an improved harmony search algorithm. J Constr Steel Res 66(5):664–669

    Article  Google Scholar 

  120. Cakiroglu C, Bekdaş G, Kim S, Geem ZW (2020) Optimisation of shear and lateral-torsional buckling of steel plate girders using meta-heuristic algorithms. Appl Sci 10(10):3639

    Article  Google Scholar 

  121. Cakiroglu C, Bekdaş G, Geem ZW (2020) Harmony search optimisation of dispersed laminated composite plates. Materials 13(12):2862

    Article  Google Scholar 

  122. Toklu YC (2004) Nonlinear analysis of trusses through energy minimization. Comput Struct 82(20–21):1581–1589

    Article  Google Scholar 

  123. Toklu YC, Bekdaş G, Temur R (2013) Analysis of trusses by total potential optimization method coupled with harmony search. Struct Eng Mech 45(2):183–199

    Article  Google Scholar 

  124. Toklu YC, Temür R, Bekdaş G (2015) Computation of nonunique solutions for trusses undergoing large deflections. Int J Comput Methods 12(03):1550022

    Article  Google Scholar 

  125. Temür R, Bekdaş G, Toklu YC (2017) Total potential energy minimization method in structural analysis considering material nonlinearity. Chall J Struct Mech 3:129–133

    Article  Google Scholar 

  126. Toklu YC, Bekdaş G, Temür R (2017) Analysis of cable structures through energy minimization. Struct Eng Mech 62(6):749–758

    Google Scholar 

  127. Toklu YC, Uzun F (2016) Analysis of tensegric structures by total potential optimization using metaheuristic algorithms. J Aerosp Eng 29(5):04016023

    Article  Google Scholar 

  128. Kayabekir AE, Toklu YC, Bekdaş G, Nigdeli SM, Yücel M, Geem ZW (2020) A novel hybrid harmony search approach for the analysis of plane stress systems via total potential optimization. Appl Sci 10(7):2301

    Article  Google Scholar 

  129. García-Segura T, Yepes V, Alcalá J (2017) Computer-support tool to optimize bridges automatically. Int J Comput Methods Exp Meas 5(2):171–178

    Google Scholar 

  130. Gholizadeh R, Amiri GG, Mohebi B (2010) An alternative approach to a harmony search algorithm for a construction site layout problem. Can J Civ Eng 37(12):1560–1571

    Article  Google Scholar 

  131. Kayhan AH, Korkmaz KA, Irfanoglu A (2011) Selecting and scaling real ground motion records using harmony search algorithm. Soil Dyn Earthq Eng 31(7):941–953

    Article  Google Scholar 

  132. Gold S, Krishnamurty S (1997) Trade-offs in robust engineering design. In: Proceedings of the ASME design engineering technical conferences, Sept 1997

    Google Scholar 

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Authors and Affiliations

  1. Department of Civil Engineering, Istanbul University-Cerrahpaşa, 34320, Avcılar, Istanbul, Turkey

    Aylin Ece Kayabekir, Gebrail Bekdaş, Melda Yücel & Sinan Melih Nigdeli

  2. College of IT Convergence, Gachon University, Seongnam, 13120, Korea

    Zong Woo Geem

Authors
  1. Aylin Ece Kayabekir
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  2. Gebrail Bekdaş
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  3. Melda Yücel
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  4. Sinan Melih Nigdeli
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  5. Zong Woo Geem
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Correspondence to Zong Woo Geem .

Editor information

Editors and Affiliations

  1. Department of Civil Engineering, Karamanoglu Mehmetbey University, Karaman, Turkey

    Serdar Carbas

  2. Department of Electrical and Electronics Engineering, Karamanoglu Mehmetbey University, Karaman, Turkey

    Abdurrahim Toktas

  3. Department of Computer Engineering, Tarsus University, Tarsus, Turkey

    Deniz Ustun

Appendix

Appendix

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Kayabekir, A.E., Bekdaş, G., Yücel, M., Nigdeli, S.M., Geem, Z.W. (2021). Harmony Search Algorithm for Structural Engineering Problems. In: Carbas, S., Toktas, A., Ustun, D. (eds) Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications. Springer Tracts in Nature-Inspired Computing. Springer, Singapore. https://doi.org/10.1007/978-981-33-6773-9_2

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