动态连续蚁群系统及其在天基预警中的应用

运筹与管理 ›› 2011, Vol. 20 ›› Issue (2): 89-96.

动态连续蚁群系统及其在天基预警中的应用

胡崇海, 李一军, 姜维, 王铁军

哈尔滨工业大学管理学院,黑龙江哈尔滨 150001

收稿日期:2010-04-19 出版日期:2011-04-25
作者简介:胡崇海(1981-),男,博士生,研究方向:智能决策、传感器调度优化;李一军(1957-),男,博士生导师,研究方向:商务智能、信息系统安全工程等。
基金资助:
高等学校博士学科点专项科研基金资助课题(200802131048)

Dynamic Continuous Ant Colony Optimization and Its Application to Space-based Warning System

HU Chong-hai, LI Yi-jun, JIANG Wei, WANG Tie-jun

School of Management, Harbin Institute of Technology, Harbin 150001, China

Received:2010-04-19 Online:2011-04-25

摘要/Abstract

摘要： 存在监控冲突的天基中段预警传感器调度优化是一个动态、高维、复杂多约束的非线性优化问题,其解空间的高维度与状态复杂性直接制约了智能优化算法的运用。本文以任务分解与任务复合优先权计算为基础,通过二级分离机制将解空间维度与状态复杂性降低至适于连续蚁群(continuous ant-colony optimization, CACO)处理的全局优化形态,构建出相应的优化子路径集.在此基础上,针对监控冲突导致的状态变化特性,从局部搜索递进与募集的角度提出适于传感器调度优化的MG-DCACO(double direction continuous ant-colony optimization based mass recruitment and group recruitment)算法,成功将智能优化算法应用于基于低轨星座的天基中段预警中.最后对算法的收敛性进行论证,并通过与已有规则调度算法的对比得出MG-DCACO算法可获得优于规则调度算法的全局最优解。

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

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 complex-constraints 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.

中图分类号:

O221.2
TP181

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.

HU Chong-hai, LI Yi-jun, JIANG Wei, WANG Tie-jun. Dynamic Continuous Ant Colony Optimization and Its Application to Space-based Warning System[J]. Operations Research and Management Science, 2011, 20(2): 89-96.

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