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An Integrated Approach for Optimum Design of Bridge Decks Using Genetic Algorithm and Artificial Neural Network

IR@SERC: CSIR-Structural Engineering Research Centre, Chennai

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Title An Integrated Approach for Optimum Design of Bridge Decks Using Genetic Algorithm and Artificial Neural Network
 
Creator Srinivas, V.
Ramanjaneyulu, K.
 
Subject T-girder bridge; Cost optimization
Genetic algorithm
Artificial neural networks
Grillage analogy
Objective function
Constraints
 
Description The objective of this paper is to develop an integrated approach using artificial neural networks (ANN) and genetic algorithms (GA) for cost optimization of bridge deck configurations. In the present work, ANN is used to predict the structural design responses which are used further in evaluation of fitness and constraint violation in GA process. A multilayer back-propagation neural network is trained with the results obtained using grillage analysis program for different bridge deck configurations and the correlation between sectional parameters and design responses has been established. Subsequently, GA is employed for arriving at optimum configuration of the bridge deck system by minimizing the total cost. By integrating ANN with GA, the computational time required for obtaining optimal solution could be reduced substantially. The efficacy of this approach is demonstrated by carrying out studies on cost optimization of Tgirder bridge deck system for different spans. The method presented in this paper, would greatly reduce the computational effort required to find the optimum solution and guarantees bridge engineers to arrive at the near-optimal solution that could not be easily obtained using general modeling programs or by trial-and-error.
 
Date 2009
2009
2007
 
Type Article
 
Identifier Advances in Engineering Software vol.38, 2007 pp.475–487
http://hdl.handle.net/123456789/34
 
Language en
 
Rights It is tried to respect the rights of the copyright holders to the best of the knowledge. If it is brought to our notice that the rights are violated then the item would be withdrawn.
 
Publisher Elsevier