摘要
基于传统任务决策方法决策空间过大的问题,建立了一种面向任务的最优化决策模型,在采用嵌套遗传算法优化任务平台分组的基础上,提出了一种通过调整内部平台分配向量和外部平台分配向量来最优化任务平台分配的向量调整法。最后对基于向量调整法的任务决策方法进行了仿真,结果表明,基于向量调整法的任务决策方法比传统决策算法具备更好的可操作性和更快的收敛速度,对提高指挥控制系统任务决策的实时性具有重要的参考价值。
As the search space of traditional Task-Platform Scheduling Optimization （TPSO） methodology is too large,a task oriented task-platform scheduling optimization model is formulated. After task-platform grouping is finished by Nested Genetic Algorithm （NGA）,a Vector Modifying Method （VMM）,which is employed to optimize task-platform scheduling by optimizing the Internal Platform Scheduling Vector（IPSV）and the External Platform Scheduling Vector（EPSV）,is put forward. At last, a TPSO scenario is simulated by the TPSO methodology based on VMM. The result shows that the TPSO methodology based on VMM performs better in both maneuverability and convergence than traditional methodology. It is also illustrated that the TPSO methodology based on VMM can be used as an important reference to improve the efficiency of TPSO for the command and control system.
出处
《火力与指挥控制》
CSCD
北大核心
2014年第8期55-60,共6页
Fire Control & Command Control
基金
航空科学基金资助项目(2011ZC53024)
关键词
最优化决策
指挥控制
决策者
平台分配
任务执行精确度
scheduling optimization
command and control
decision maker
task-platform scheduling
task processing accuracy
