摘要
针对协同优化过程对初始点敏感以及容易陷入局部最优点的问题,提出了一种改进的协同优化算法。改进后的协同优化算法综合考虑学科级优化设计点与系统级设计点的距离以及子学科级内部最优设计点,能较好地减弱优化结果对初始点以及松弛因子选择的依赖性,更容易找到优化问题全局最优设计点。最后,通过两个经典算例验证了改进算法的有效性及稳定性。
Regarding the problems that the process of optimization is sensitive to the initial point and easily trapped into local optimum, we propose an improved collaborative optimization algorithm. The proposed algorithm takes into account of the distance between the disciplinary level design point and and the system level internal design point, as well as the disciplinary level＇s optimal design point. Besides, it can weaken the dependence of optimization results on the relaxing factor and the initial point, and find the optimal design point using the least times of optimization iteration. Two classical examples verify the effectiveness and stability of our proposal.
出处
《计算机工程与科学》
CSCD
北大核心
2016年第11期2310-2313,共4页
Computer Engineering & Science
基金
国家自然科学基金(61304211
61375078)
关键词
协同优化
松弛因子
初始点
collaborative optimization
relaxing factor
initial point
