福州大学学报（自然科学版）2018，Vol.46Issue(3)：379-385,7.DOI:10.7631/issn.1000-2243.17298
模拟退火法在协同优化中的应用
An application of simulated annealing to collaborative optimization
摘要
Abstract
In order to deal with the shortcoming of traditional collaborative optimization, for example the results are always not converging and local optimal solution;an improved collaborative optimization based on simulated annealing is presented. Under the premise of the advantages of the parallel and autonomy of the standard collaborative optimization algorithm, the ASA-MMFD-CO replaces the single optimization algorithm by the hybrid optimization strategy based on the global algorithm ASA and the gradient algorithm MMFD in the system level. Meanwhile, dynamic relaxation factor is used in the optimization. The global optimization and accuracy can be guaranteed, and the shortcoming of tradi-tional collaborative optimization can be resolved. Two typical MDO examples are adopted to test the improved CO. The results show that it has better accuracy, convergence rate and stability.关键词
协同优化/模拟退火/组合优化/动态松弛Key words
collaborate optimization/simulated annealing/hybrid optimization/dynamic relaxation分类
机械制造引用本文复制引用
饶太春,兰林强,罗伟林..模拟退火法在协同优化中的应用[J].福州大学学报（自然科学版）,2018,46(3):379-385,7.基金项目
福建省海洋高新产业发展专项基金资助项目(闽海洋高新[2016]16号) （闽海洋高新[2016]16号）
福建省教育厅省属高校专项基金资助项目(JK2015003) （JK2015003）
