Artificial Bee Colony (ABC) algorithm in the design optimization of RC continuous beams

Industrial Application

Abstract

The objective of this study is to obtain the optimum design for reinforced concrete continuous beams in terms of cross section dimensions and reinforcement details using a fine tuned Artificial Bee Colony (ABC) Algorithm while still satisfying the constraints of the ACI Code (2008). The ABC algorithm used in this paper has been slightly modified to include a Variable Changing Percentage (VCP) that further improves its performance when dealing with members consisted of multiple variables. The objective function is the total cost of the continuous beam which includes the cost of concrete, formwork and reinforcing steel bars. The design variables used are beam width, beam height, number and diameter of: bottom continuous reinforcing bars, bottom cutoff reinforcing bars, top continuous reinforcing bars and top cutoff reinforcing bars as well as the diameter of stirrups. Four RC beams of varying complexity are presented and optimized. The first three beams are used to fine tune the control parameters of the ABC algorithm, whereas the fourth beam was previously optimized by Arafa et al. (J Artif Intell 76–88, 2011) and is presented here to prove the superiority of this relatively new optimization algorithm.

Keywords

Optimization RC Beams Artificial Bee Colony 

References

  1. ACI Committee 318 (2008) Building code requirements for structural concrete (ACI 318-08), American Concrete Institute. Farmington Hills, MichGoogle Scholar
  2. Akin A, Saka MP (2010) Optimum detailed design of reinforced concrete continuous beams using the harmony search algorithm. In: 10th international conference on computational structures technology. Civil-Comp Press, StirlingshireGoogle Scholar
  3. Arafa M, Alqedra M, Ismail M (2011) Optimum design of prestressed reinforced concrete beams using genetic algorithms. J Artif Intell 4(1):76–88CrossRefGoogle Scholar
  4. Barros H, Martins RAF, Barros AFM (2005) Cost optimization of singly and doubly reinforced concrete beams with EC2-2001. Struct Multidisc Optim 30(3):236–242CrossRefGoogle Scholar
  5. Barros AFM, Barros MH, Ferreira C (2012) Optimal design of rectangular RC sections for ultimate bending strength. Struct Multidisc Optim 45(6):845–860MathSciNetCrossRefGoogle Scholar
  6. Camp C, Pazeshk S, Hansson H (2003) Flexural design of reinforced concrete frames using a genetic algorithm. J Struct Eng 129(1):105–115CrossRefGoogle Scholar
  7. Chakrabarty BK (1992) A model for optimal design of reinforced concrete beam. J Struct Eng ASCE 11(118):3238–3280CrossRefGoogle Scholar
  8. Chou T (1977) Optimum reinforced concrete T-beam sections. J Struct Div 8(103):1605–1622Google Scholar
  9. Coello CA, Christiansen AD, Hernandez F (1997) A simple genetic algorithm for the design of reinforced concrete beams. Eng Comput 13(4):185–196CrossRefGoogle Scholar
  10. Ferreira C, Barros H, Barros AFM (2003) Optimal design of reinforced concrete T-sections in bending. Eng Struct 25(7):951–964CrossRefGoogle Scholar
  11. Friel L (1974) Optimum singly reinforced concrete sections. ACI J 71(11):556–564Google Scholar
  12. Hadidi A , Kazemzadeh S (2010) Structural optimization using artificial bee colony algorithm. In: 2nd international conference on engineering optimizationGoogle Scholar
  13. Kanagasundram S, Karihaloo BL (1991) Minimum cost reinforced concrete beams and columns. Comput Struct 3(41):509–527CrossRefGoogle Scholar
  14. Karaboga D (2005) An idea based on honey bee swarm for numerical optimization. Technical Report TR06. 2005: Erciyes UniversityGoogle Scholar
  15. Karaboga D, Basturk B (2008) Artificial Bee Colony (ABC) optimization algorithm for solving constrained optimization problems. Adv Soft Comput 4529:687–697CrossRefGoogle Scholar
  16. Kaveh A, Sabzi O (2011) A comparative study of two meta-heuristic algorithms for optimum designs of reinforced concrete frames. Struct Eng 9(3):193–206Google Scholar
  17. Kirsch U (1983) Multilevel optimum design of reinforced concrete structures. Eng Optim 4(6):207–219CrossRefGoogle Scholar
  18. Koumousis VK, Arsenis SJ (1998) Genetic algorithms in optimal detailed design of reinforced concrete members. Comput-Aided Civil Infrastruct Eng 13:43–52CrossRefGoogle Scholar
  19. Lee K, Geem Z (2005) A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice. Comput Methods Appl Mech Eng 194:3902–3933MATHCrossRefGoogle Scholar
  20. Lepš M, Šejnoha M (2003) New approach to optimization of reinforced concrete beams. Comput Struct 81:1957–1966CrossRefGoogle Scholar
  21. MATLAB (2010) MATLAB the language of technical computing. Version 2010. MathWorks Inc, NatickGoogle Scholar
  22. Parakash A, Agarwala SK, Singh KK (1988) Optimum design of reinforced concrete sections. Comput Struct 4(30):1009–1020CrossRefGoogle Scholar
  23. Paya-Zaforteza I, Yepes V, Hospitaler A, Gonzalez-Vidosa F (2009) CO2-optimization of reinforced concrete frames by simulated annealing. Eng Struct 31(7):1501–1508CrossRefGoogle Scholar
  24. Ramasamy JV, Govindaraj V (2005) Optimum detailed design of reinforced concrete continuous beams using genetic algorithms. Comput Struct 84(1–2):34–48Google Scholar
  25. Wight JK, MacGregor JG (2008) Reinforced concrete mechanics and design, 5th edn. Prentice Hall, Englewood Cliffs, NJGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Civil EngineeringThe Islamic University of GazaGazaPalestine

Personalised recommendations