One Optimizing Method for Moments of Inertia Applied with Improved Adaptive Genetic Algorithm

摘要：

In this paper, a new optimizing method for the moments of inertia of a mechanical structure was advanced. First, a new optimal model for the moments of inertia was advanced, which only involved with single objective and single variable, in order to reduce the calculating complexity of traditional multi-objective and multi-constrained optimizing model for the moments of inertia;Then, a new strategy for the probability selection of the crossover and mutation operation was improved to form the IAGA. The calculating results proved that, comparing to the Standard Genetic Algorithm (SGA), the IAGA improved in this paper had the advantage of converging faster, more powerfully searching, and less possible of falling into the local optimum. By that, the feasibility of the method advanced in this paper was demonstrated.

关键词： Moments of inertia Optimizing Genetic algorithm Crossover and mutation probability

作者: Heng Hui Sun Min Zhou Luo Xiang Dong Shi Hong Zha

作者单位: Institute of Intelligent Machines, Shu ShanHu Road 350,ShuShan District, Hefei, Anhui Province,China

会议类型: 国际会议

会议名称: 2011 International Conference on Mechatronics and Materials Processing(2011年机电一体化与材料加工国际会议 ICMMP)

会议地点: 广州

会议语种:英文

页码: 54-57

在线出版日期: 2011-11-18（万方平台首次上网日期，不代表论文的发表时间）