An Improved Genetic Algorithm for Structural Optimization Design

摘要：

This paper proposes an improved genetic algorithM (IGA) to enhance the performance of the simple GA for structure optimization design. The optimization design of structure with discrete variables is generally a combinatorial optimization problem. Being simple genetic algorithm has the defects of premature phenomenon, slow convergence speed and poor stability. An IGA was proposed to overcome simple GAs inherent deficiency by adopting adaptive crossover rate and mutation rate, penalty function and relative difference quotient as one operator in the search of GA. A numerical example of a 25-bar frame was given to demonstrate the validity and feasibility of IGA in its applicatioa and the experimental results show that the improved GA can obtain better results than other optimal design methods in structure optimization design.

关键词： Improved. Genetic Algorithm Relative Difference Quotient Optimization Design

作者: Guofu Sun Shucai Li Xuejun Zhou Bo Zhang

作者单位: Geotechnical and Structural Engineering Research Center, Shandong University, Jinan 250061, P.R. Chi Geotechnical and Structural Engineering Research Center, Shandong University, Jinan 250061, P.R. Chi School of Civil Engineering, Shandong Jianzhu University, Jinan 250101, P.R. China

会议类型: 国际会议

会议名称: The First World Congress on Global Optimization in Engineering & Science(第一届工程与科学全局优化国际会议 WCGO2009)

会议地点: 长沙

会议语种:英文

页码: 815-821

在线出版日期: 2009-06-01（万方平台首次上网日期，不代表论文的发表时间）