运筹与管理2011，Vol.20Issue(2)：89-96,8.
动态连续蚁群系统及其在天基预警中的应用
Dynamic Continuous Ant Colony Optimization and Its Application to Space-based Warning System
摘要
Abstract
The scheduling method of sensors on space-based warning in middle age is a dynamic, multi-dimensional, complex-constraints nonlinear optimization problem.Considering the monitoring conflict, it is nearly impossible to use intelligent optimization algorithms in this problem.On the basis of task decomposition and task multiplex priority, by means of second-stage separating, this paper reduces the multi-dimensional and complexconstraints to a suitable area.Then, through the angles of monitoring conflict, area searching and collecting, the author puts forward a MG-DCACO ( double direction continuous ant-colony optimization based mass recruitment and group recruitment) algorithm which can be used in sensors scheduling.At last, it is proved that, the MG-DCACO is convergence and outperforming the other algorithms of sensors scheduling.关键词
管理科学与工程/蚁群系统/动态优化/任务分解/天基预警Key words
management science and engineering/ dynamic continuous ant colony optimization/ dynamic optimization/ task decomposition/ space-based warning分类
数理科学引用本文复制引用
胡崇海,李一军,姜维,王铁军..动态连续蚁群系统及其在天基预警中的应用[J].运筹与管理,2011,20(2):89-96,8.基金项目
高等学校博士学科点专项科研基金资助课题(200802131048) （200802131048）
