Cost optimization of three-dimensional beamless reinforced concrete shear-wall systems via genetic algorithm

In this present work, a cost optimization has been done for r/c structural system by genetic algorithm method. In the optimization problem the shear-wall dimensions has been considered as design variables and it has been aimed at searching the optimum shear-wall dimensions that minimize total material cost of shear-wall. The constraints of structural optimization problem are constructed according to the requirements of the r/c specification so-called as ''TS 500'' and the seismic code of Turkey which is put into effect on 1998. The standard structural design procedure requires the predetermination of the dimensions of load carrying members that is generally based on designer's engineering skill, experience and intuition. In practical design applications, final dimensions are generally selected as one of the most suitable ones among numerous design selections that satisfy the regulations. However, the most of these design alternatives may not be economical, and the most economical design could only be provided by a more elaborated optimization procedure. A computer program is also developed for determining the optimum shear-wall dimensions for the minimum cost design of structural systems. The proposed algorithm minimizes structural cost including the cost of concrete and the reinforcement, wherein the costs related to transportation, workmanship and formwork prices are not included. An 13 story and beamless shear-wall system is presented as a numerical example.

[1]  Michal Šejnoha,et al.  New approach to optimization of reinforced concrete beams , 2000 .

[2]  M. Y. Rafiq,et al.  Genetic algorithms in optimal design and detailing of reinforced concrete biaxial columns supported by a declarative approach for capacity checking , 1998 .

[3]  Dan M. Frangopol,et al.  Optimum design of shear-wall systems , 1991 .

[4]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[5]  V. K. Sehgal,et al.  Least-cost design of singly and doubly reinforced concrete beam using genetic algorithm optimized artificial neural network based on Levenberg–Marquardt and quasi-Newton backpropagation learning techniques , 2007 .

[6]  Sundaramoorthy Rajasekaran,et al.  Artificial neural network and genetic algorithm for the design optimizaton of industrial roofs —A comparison , 1996 .

[7]  Seamus D. Garvey,et al.  A COMBINED GENETIC AND EIGENSENSITIVITY ALGORITHM FOR THE LOCATION OF DAMAGE IN STRUCTURES , 1998 .

[8]  Chung-Wei Feng,et al.  Using genetic algorithms to solve construction time-cost trade-off problems , 1997 .

[9]  Shahram Pezeshk,et al.  Design of Nonlinear Framed Structures Using Genetic Optimization , 2000 .

[10]  S. Rajeev,et al.  Discrete Optimization of Structures Using Genetic Algorithms , 1992 .

[11]  Ashraf F. Ashour,et al.  Cost optimisation of reinforced concrete flat slab buildings , 2005 .

[12]  Mehmet Polat Saka,et al.  Optimum Design of Grillage Systems Using Genetic Algorithms , 1998 .

[13]  Alain Vautrin,et al.  Weight minimization of composite laminated plates with multiple constraints , 2003 .

[14]  J. V. Ramasamy,et al.  Optimum detailed design of reinforced concrete continuous beams using Genetic Algorithms , 2005 .

[15]  Maria do Carmo Nicoletti,et al.  Using a modified genetic algorithm to minimize the production costs for slabs of precast prestressed concrete joists , 2007, Eng. Appl. Artif. Intell..