摘要
几何约束求解的方法关系到特征造型系统的性能,为提高几何约束求解的速度,将和声搜索算法应用于几何约束求解中。通过优先选择较小的和声库,利用最好解的评价值确定微调扰动的幅度,并将其嵌入到拉斯维加斯算法中,提高了和声搜索算法的性能。实验结果表明,改进的和声算法具有自适应性,能有效克服局部收敛问题,提高了求解速度。
Performance of feature modeling system relates to methods of geometric constraint solving.To improve the speed of geometric constraint solving,this paper applied harmony search algorithm to the geometric constraint solving.In order to increase performance of harmony search algorithm,selected a smaller harmony memory size preferentially,employed the assessment value of the best solution to determine the range of the fine-tuning disturbance,and embedded it into the Las Vegas algorithm.Experimental results show that the improved algorithm is adaptive,and that can overcome the problem of local convergence effectively,while improving the speed of the solution.
出处
《计算机应用研究》
CSCD
北大核心
2010年第7期2773-2775,2779,共4页
Application Research of Computers
基金
国家自然科学基金资助项目(60173055)
关键词
特征造型
几何约束求解
和声搜索算法
拉斯维加斯算法
自适应微调扰动
feature-based modeling
geometric constraint solving
harmony search algorithm
Las Vegas algorithm
adaptive fine-tune the disturbance