计算机工程与科学2017，Vol.39Issue(9)：1736-1741,6.DOI:10.3969/j.issn.1007-130X.2017.09.021
一种具有全局快速寻优的多学科协同优化方法
Improved multidisciplinary collaborative optimization with global fast optimization
摘要
Abstract
We propose a new collaborative optimization (CO) method with global fast optimization to solve the problems of too many times of iterations and local optimal solutions of CO.A new slack factor is introduced into system optimization,and optimal design points can be fast converged to extreme points by the improved dynamic slack factor.Static slack factor enables optimal design points to jump out of local extreme points,guaranteeing that the results of the system objective function are global optimal solutions.The objective function of subsystem is divided into two parts:consistent objective function and subsystem optimal objective function,which are added up with different weights as the subsystem objective function.Thus both the consistence and the independence of subsystems are taken into account.The improved CO (ICO) is validated via the examples of reducer.Simulation results show that on the premise of ensuring a smaller constrained maximum value,the ICO can quickly get the global optimal solution and has good robustness.关键词
协同优化/松弛因子/一致性/稳定性Key words
collaborative optimization/slack factor/consistency/stability分类
信息技术与安全科学引用本文复制引用
黄仕贵,郑松,葛铭,魏江..一种具有全局快速寻优的多学科协同优化方法[J].计算机工程与科学,2017,39(9):1736-1741,6.基金项目
国家自然科学基金(61304211,61375078) （61304211,61375078）
