摘要
针对机构综合的非线性方程组求解问题提出了一种改进的微分进化算法.该算法是将方程组转换成一个优化问题,在进化过程中,该算法根据进化情况采用动态参数调整机制提高算法的搜索效率,并且对种群重叠状况进行实时监视,对重叠个体利用混沌搜索策略来进一步提高算法的全局寻优能力.机构综合实例结果分析表明,文中提出的改进微分进化算法高效、且全局寻优能力强.
Aiming at solving the nonlinear equations of mechanism synthesis is presented, an improved differential evolution （DE）algorithm is proposed. The equations are transformed into an optimization problem. During the evolution, according to evolution condition in the proposed algorithm the dynamic parameter adjustment mechanism is adopted to enhance its search efficiency, the population overlap is monitored in real-time mode; for overlapped individual, by use of chaotic search strategy the global optimal searching ability of the proposed algorithm is further improved. The results of mechanism synthesis show that the proposed algorithm is efficient and possesses strong global optimal searching ability.
出处
《湖南文理学院学报（自然科学版）》
CAS
2009年第2期65-68,共4页
Journal of Hunan University of Arts and Science(Science and Technology)
基金
湖南省"十一五"重点建设学科(机械设计及理论)(湘教通2006180)
国家自然科学基金(50845038)
湖南省普通高校学科带头人(湘教通[2008]315))
关键词
机构综合
微分进化
优化
混沌
智能优化
mechanism synthesis
differential evolution
optimization
chaos
intelligent optimization
