Computational & Technology Resources
an online resource for computational,
engineering & technology publications |
|
Civil-Comp Proceedings
ISSN 1759-3433 CCP: 100
PROCEEDINGS OF THE EIGHTH INTERNATIONAL CONFERENCE ON ENGINEERING COMPUTATIONAL TECHNOLOGY Edited by: B.H.V. Topping
Paper 52
Improving the Big Bang-Big Crunch Algorithm for Optimum Design of Steel Frames O. Hasançebi and S. Kazemzadeh Azad
Department of Civil Engineering, Middle East Technical University, Ankara, Turkey , "Improving the Big Bang-Big Crunch Algorithm for Optimum Design of Steel Frames", in B.H.V. Topping, (Editor), "Proceedings of the Eighth International Conference on Engineering Computational Technology", Civil-Comp Press, Stirlingshire, UK, Paper 52, 2012. doi:10.4203/ccp.100.52
Keywords: steel frames, practical design, metaheuristics, big bang-big crunch algorithm, discrete optimization.
Summary
Performance enhancement of the existing metaheuristic algorithms for tackling specific optimization problems has become one of the most frequent strategies in recent years. This paper presents an improved version of the big bang-big crunch (BB-BC) algorithm [1] namely the exponential BB-BC algorithm (EBB-BC) for optimum design of steel frames according to ASD-AISC [2] provisions. It is shown that the standard version of the algorithm sometimes is unable to provide reasonable solutions for problems of the discrete design optimization of steel frames. Therefore, by investigating the shortcomings of the BB-BC algorithm, it is proposed to enhance the performance of the algorithm for solving complicated steel frame optimization problems. The proposed EBB-BC algorithm utilizes the advantages of a recently developed third power formulation of the BB-BC algorithm. The rationale behind the use of the third power formulation is to achieve a satisfactory trade-off or compromise between the following two conflicting requirements needed to eliminate the shortcomings of the standard formulation: (i) the diminishing search dimensionality in the beginning of the search process and increasing it somewhat towards the latest stage and (ii) enabling a large step size from time to time at later optimization stages to facilitate design transitions to new design regions and thereby preventing entrapment of the search in local optima.
In this paper, the use of an exponentially distributed random number for generating the new candidate solutions is proposed and investigated in design optimization of a benchmark 132-member unbraced steel frame [3]. In order to evaluate the performance of the proposed algorithm, the optimization results attained using the EBB-BC algorithm are compared to those of other well known metaheuristics. The numerical results clearly demonstrate the efficiency and robustness of the proposed EBB-BC algorithm as a novel version of the well known BB-BC technique in solving practical design optimization instances of steel frames. References
purchase the full-text of this paper (price £20)
go to the previous paper |
|