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Bat algorithm for optimization of reinforced concrete columns
Author(s) -
Bekdas Gebrail,
Nigdeli Sinan Melih
Publication year - 2016
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.201610329
Subject(s) - harmony search , structural engineering , moment (physics) , ultimate tensile strength , computer science , metaheuristic , buckling , flexural strength , algorithm , mathematical optimization , mathematics , materials science , engineering , composite material , physics , classical mechanics
In structural mechanics, when the design contains two different materials with opposite mechanical behaviours and costs, the optimum design cannot exactly found. In that case, numerical optimization algorithms are a good source. Reinforced concrete design shows that behaviour since concrete is a cheap material comparing to steel while the tensile strength of concrete is very low to use. The cross sections are effective on the stresses and balance of tensile and compressive forces. This situation shows the importance of the dimension optimization of reinforced concrete members. Also, the number and size of the reinforcements need an optimization. The place of the reinforcements is effective on the place of tensile forces in the calculation of axial force and flexural moment capacity. In this paper, reinforced concrete columns are optimized for the cost minimization by employing a bio‐inspired metaheuristic algorithm called bat algorithm. The idealization of the echolocation behaviour of bats is the inspiration of the bat algorithm. Differently from the algorithms, the bat algorithm uses global and local optimization with a changeable probability. The optimization process considers the security measures and slenderness of the according to the design regulation called ACI 318. The slenderness is taken into consideration by using a magnified design flexural moment, which is factored by a value defined according to the buckling load and axial load of columns. The proposed approach is applied for different numerical cases and the results are compared with the approach using harmony search algorithm. The present approach is effective for the optimization problem. (© 2016 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)