Paper Title:
Optimization of Reinforced Concrete Tall Buildings Using a Hybrid Genetic Algorithm
  Abstract

Tall buildings play an important role in the modern urban city, where only a few lands are available for the increasing population. In this study a hybrid genetic algorithm (GA) and optimality criteria (OC) method is presented for the optimum design of tall buildings under multi-load cases based on the current Chinese design codes. The entire optimum design procedure is divided into two parts: strength optimum design and stiffness optimum design. Member depths are treated as design variables. A GA with the strategy of adaptive feasible region is proposed to perform the discrete optimization of tall buildings under the strength constraints with the results of the stiffness optimum design as the lower bounds of the member size. The optimum stiffness design is conducted using OC method with the results of the strength optimum design as the lower bounds of the member size. This procedure is repeated until convergence is obtained. A design example is optimized to demonstrate the practicability and effectiveness of the proposed method

  Info
Periodical
Chapter
Chapter 2: Monitoring and Control of Structures
Edited by
Xuejun Zhou
Pages
815-819
DOI
10.4028/www.scientific.net/AMM.94-96.815
Citation
H. Y. Lu, X. Guo, "Optimization of Reinforced Concrete Tall Buildings Using a Hybrid Genetic Algorithm", Applied Mechanics and Materials, Vols. 94-96, pp. 815-819, 2011
Online since
September 2011
Authors
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Price
$32.00
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