Skip to main content

Advertisement

Log in

Optimum Design of Steel Frames Using Different Variants of Differential Evolution Algorithm

  • Research Paper
  • Published:
Iranian Journal of Science and Technology, Transactions of Civil Engineering Aims and scope Submit manuscript

Abstract

A differential evolution (DE)-based algorithm is used for discrete optimization of steel frames. DE is a simple yet efficient population-based search algorithm, originally proposed for continuous optimization problems. It is based on the same search philosophy as most evolutionary algorithms (EA), utilizing mutation, crossover and selection operators. However, unlike traditional EAs, the DE creates new candidate solutions by perturbing the parent individual with the weighted difference of several other randomly chosen individuals of the same population. In this study, performance of DE in optimal design of steel frames is investigated. Eleven different variants of DE are tested through three benchmark problems. The comparison results between the DE and other metaheuristic algorithms, such as genetic algorithm (GA), ant colony optimizer (ACO) and particle swarm optimizer (PSO) methods, taken from the literature, show that in most cases the DE can perform as well as other techniques. It is found that two particular variants of DE, namely ‘DE/best/1’ and ‘DE/best/1 with jitter’ provide better results compared to the other variants. In both variants, the best in the iteration is selected as the base vector of DE algorithm for perturbation in mutation stage. Also, results show that low values for control parameter CR, can yield better designs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

References

  • American Institute of Steel Construction (AISC). Manual of steel construction load resistance factor design. 3rd ed. Chicago: AISC; 2001.

  • Camp C, Pezeshk S, Cao G (1998) Optimized design of two-dimensional structures using genetic algorithm. J Struct Eng ASCE 124(5):551–559

    Google Scholar 

  • Camp CV, Bichon BJ, Stovall SP (2005) Design of steel frames using ant colony optimization. J Struct Eng ASCE 131(3):369–379

    Google Scholar 

  • Coello Coello CA (2002) Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art. Comput Methods Appl Mech Eng 191:1245–1287

    MathSciNet  MATH  Google Scholar 

  • Degertekin SO (2007) A comparison of simulated annealing and genetic algorithm for optimum design of nonlinear steel space frames. Struct Multidisc Optim 34:347–359

    Google Scholar 

  • Degertekin SO (2008) Optimum design of steel frames using harmony search algorithm. Struct Multidisc Optim 36:393–401

    Google Scholar 

  • Degertekin SO, Saka MP, Hayalioglu MS (2008) Optimal load and resistance factor design of geometrically nonlinear steel space frames via tabu search and genetic algorithm. Eng Struct 30:197–205

    Google Scholar 

  • Dogan E, Saka MP (2011) Optimum design of unbraced steel frames to LRFD–AISC using particle swarm optimization. Adv Eng Softw. https://doi.org/10.1016/j.advengsoft.2011.05.008

    Article  Google Scholar 

  • Dumonteil P (1992) Simple equations for effective length factors. Eng J AISC 29(3):111–115

    Google Scholar 

  • Foley CM, Schinler D (2003) Automated design of steel framesusing advanced analysis and object-oriented evolutionary computation. J Struct Eng ASCE 129(5):648–660

    Google Scholar 

  • Gerist S (2019) Maheri MR Structural damage detection using imperialist competitive algorithm. Appl Soft Comput 77:1–23

    Google Scholar 

  • Gerist S, Maheri MR (2016) Multi-stage approach for structural damage detection problem using basis pursuit and particle swarm optimization. J Sound Vibr 384:210–226. https://doi.org/10.1016/j.jsv.2016.08.024

    Article  Google Scholar 

  • Hasançebi O, Çarbas S, Saka MP (2010) Improving the performance of simulated annealing in structural optimization. Struct Multidisc Optim 41:189–203

    Google Scholar 

  • Hayalioglu MS (2001) Optimum load and resistance factor design of steel space frames using genetic algorithm. Struct Multidisc Optim 21:292–299

    Google Scholar 

  • Jarmai K, Snyman JA, Farkas J, Gondos G (2003) Optimal design of a welded I-section frame using four conceptually different optimization algorithms. Struct Multidisc Optim 25:54–61

    Google Scholar 

  • Kargahi M, Anderson JC, Dessouky MM (2006) Structural weight optimization of frames using tabu search. I: optimization procedure. J Struct Eng ASCE 132(12):1858–1868

    Google Scholar 

  • Kaveh A, Bakhshpoori T (2013) Optimum design of steel frames using Cuckoo Search algorithm with Lévy flights. Tall Build Special Struct 22(13):1023–1036

    Google Scholar 

  • Kaveh A, Bolandgerami A (2017) Optimal design of large scale space steel frames using cascade enhanced colliding body optimization. Struct Multidiscip Optim 55:237–256

    Google Scholar 

  • Kaveh A, Ilchi GM (2018) Optimum seismic design of 3D irregular steel frames recently developed modern meta-heuristic algorithms. Comput Civ Eng 32(3):1–9

    Google Scholar 

  • Kaveh A, Talatahari S (2008) A discrete particle swarm ant colony optimization for design of steel frames. Asian J Civ Eng 6(9):531–542

    Google Scholar 

  • Kaveh A, Talatahari S (2010a) Optimum design of skeletal structures using imperialist competitive algorithm. Comput Struct 88:1220–1229

    MATH  Google Scholar 

  • Kaveh A, Talatahari S (2010b) Optimal design of skeletal structures via the charged system search algorithm. Struct Multidisc Optim 41:893–911

    Google Scholar 

  • Kaveh A, Talatahari S (2010c) An improved ant colony optimization for the design of planar steel frames. Eng Struct 32:864–873

    MATH  Google Scholar 

  • Kaveh A, Talatahari S (2012) Charged system search for optimal design of planar frame structures. Appl Soft Comput 12(1):382–393

    Google Scholar 

  • Kaveh A, Zakian P (2014) Seismic design optimisation of RC moment frames and dual shear wall-frame structures via CSS algorithm. Asian J Civ Eng 15:435–465

    Google Scholar 

  • Kaveh A, Fahimi-Farzam M, Kalateh-Ahani M (2015a) Performance-based multi-objective optimal design of steel frame structures: nonlinear dynamic procedure. Sci Iran 22(2):373–387

    Google Scholar 

  • Kaveh A, Fahimi-Farzam M, Kalateh-Ahani M (2015b) Optimum design of steel frame structures considering economic cost and damage index. Smart Struct Syst Technol 16(1):1–26

    Google Scholar 

  • Kaveh A, Hoseini Vaez SR, Hosseini P (2017) Modified dolphin monitoring operator for weight optimization of frame structures. Period Polytech Civ Eng 61(4):770–779

    Google Scholar 

  • Kitayama S, Arakawa M, Yamazakia K (2011) Differential evolution as the global optimization technique and its application to structural optimization. Appl Soft Comput 11:3792–3803

    Google Scholar 

  • Lagaros ND, Papadrakakis M, Kokossalakis G (2002) Structural optimization using evolutionary algorithms. Comput Struct 80:571–589

    Google Scholar 

  • Li LJ, Huang ZB, Liu F, Wu QH (2007) A heuristic particle swarm optimizer for optimization of pin connected structures. Comput Struct 85:340–349

    Google Scholar 

  • Maheri MR, Narimani M (2014) An enhanced harmony search algorithm for optimum design of side sway steel frames. Comput Struct 136:78–89

    Google Scholar 

  • Maheri MR, Talezadeh M (2018) An enhanced imperialist competitive algorithm for optimum design of skeletal structures. Swarm Evol Comput 40:24–36

    Google Scholar 

  • Maheri MR, Askarian M, Shojaee S (2016) Size and topology optimization of trusses using hybrid genetic-particle swarm algorithms. Iran J Sci Technol Trans Civ Eng 40(3):179–193

    Google Scholar 

  • Maheri MR, Shokrian H, Narimani MM (2017) An enhanced honey bee mating optimization algorithm for design of side sway steel frames. Adv Eng Softw 109:62–72

    Google Scholar 

  • Makiabadi H, Maheri MR (2020) An enhanced symbiotic organism search algorithm (ESOS) for the sizing design of pin connected structures. Iran J Sci Eng Trans Civ Eng. https://doi.org/10.1007/s40996-020-00471-0

    Article  Google Scholar 

  • Makiabadi MH, Maheri MR (2021) An enhanced symbiotic organism search algorithm for design optimization of trusses. Adv Struct Eng. https://doi.org/10.1177/13694332211026219

    Article  Google Scholar 

  • Pezeshk S, Camp CV, Chen D (2000) Design of nonlinear framed structures using genetic algorithms. J Struct Eng ASCE 126(3):382–388

    Google Scholar 

  • Prendes Gero MB, Bello García A, del Coz Díaz JJ (2005) A modified elitist genetic algorithm applied to the design optimization of complex steel structures. J Construct Steel Res 61:265–280

    Google Scholar 

  • Prendes Gero MB, Bello García A, del Coz Díaz JJ (2006) Design optimization of 3D steel structures: Genetic algorithms vs classical techniques. J Construct Steel Res 62:1303–1309

    Google Scholar 

  • Price KV, Storn R, Lampinen J (2005) Differential evolution—a practical approach to global optimization. Springer, Berlin

    MATH  Google Scholar 

  • Safari D, Maheri MR, Maheri A (2011) Optimum design of steel frames using a multiple-deme GA with improved reproduction operators. J Construct Steel Res 67:1232–1243

    Google Scholar 

  • Safari D, Maheri MR, Maheri A (2013) On the performance of a modified multiple-deme genetic algorithm in LRFD design of steel frames. Iran J Sci Tech Trans Civ Eng 37(C2):169–190

    Google Scholar 

  • Storn R, Price KV (1997) Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces. J Glob Optim 11:341–359

    MathSciNet  MATH  Google Scholar 

  • Wu CY, Tseng KY (2010a) Truss structure optimization using adaptive multi-population differential evolution. Struct Multidisc Optim 42:575–590

    Google Scholar 

  • Wu CY, Tseng KY (2010b) Topology optimization of structures using modified binary differential evolution. Struct Multidisc Optim 42:939–953

    Google Scholar 

  • Yun YM, Kim BH (2005) Optimum design of plane steel frame structures using second-order inelastic analysis and a genetic algorithm. J Struct Eng ASCE 131(12):1820–1831

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mahmoud R. Maheri.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Safari, D., Maheri, M.R. & Maheri, A. Optimum Design of Steel Frames Using Different Variants of Differential Evolution Algorithm. Iran J Sci Technol Trans Civ Eng 45, 2091–2105 (2021). https://doi.org/10.1007/s40996-021-00711-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40996-021-00711-x

Keywords

Navigation