Applying genetic algorithms to steel-reinforced concrete elements optimization design problems

• Main Authors: Sung,Kong-Ching, 宋孔慶
• Other Authors: Chen,Chen-Cheng
• Format: Others
• Language: zh-TW
• Published: 1996
• Online Access: http://ndltd.ncl.edu.tw/handle/27630892810809794076

碩士 === 國立臺灣大學 === 土木工程研究所 === 84 === 　　The structural optimization design problems are usually con-strainted, nonlinear and discrete in type. Thus the traditional methods, such as gradient-based methods and linear programming, are not suitable for these problems. This research tried to apply a genetic optimization system to the structural optimiza-tion design problems of tension-reinforced concrete beam, doubly reinforced concrete beam, and beam column respectly. 　　"Genetic Algorithm" is a computational method which mimics the evolution in nature, and it is proved to be robust for its ability to find the global optimum of multi-modal problems. 　　Fur-thermore, it can be used to solve combinatorial problems and scheduling problems via the encoding process. This research has built a genetic ptimization system by using techniques of object-oriented programming, and drawn a series of procedures to make use of this system to solve optimization problems. 　　Comparing the results to the solutions of exhaustive search, it shows that genetic algorithms are far more efficient than ex-haustive search and there is only 4% average error between each. So it can be concluded that genetic algorithms are practical methods for solving combinatorial optimization design problems.