Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Engineering Applications of Artificial Intelligence
Optimum detailed design of reinforced concrete continuous beams using Genetic Algorithms
Computers and Structures
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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.