基于多目标算法的空中作战任务规划框架研究  

Research on Air Combat Mission Planning Based on Multi-target Algorithm

作　　者：郭昱普 蔡飞[1] 潘志强 GUO Yu-pu;CAI Fei;PAN Zhi-qiang(Science and Technology on Information Systems Engineering Laboratory,National University ofDefense Technology,Changsha 410073,China)

机构地区：[1]国防科技大学信息系统工程重点实验室

出　　处：《导航定位与授时》2019年第5期25-31,共7页Navigation Positioning and Timing

基　　金：国防基础科研计划(JCKY2017204B064)

摘　　要：空中作战任务规划是一项复杂的任务,随着空中作战飞行器的种类、数量及其之间交互性的增加,任务规划也变得越来越复杂。任务规划人员必须在有限的时间内制定出最优的任务分配策略。决策支持工具可以辅助任务规划人员找到最优的规划方案。介绍了设计多目标进化算法以及在空中作战任务规划领域的框架和工作流程,具体的任务包括空中打击动态目标的定位问题和情报监视侦察(ISR)任务规划。总结了这些研究的经验教训,探讨了未来可能的发展方向。Air combat mission planning is a complex task. With the increase of the type, number and interactivity of air combat aircraft, the task planning will become more and more complex. The task planners must work out the optimal task allocation strategy within the limited time. Decision support tools can assist task planners to find the optimal planning scheme. This paper introduces the framework and workflow of applying multi-objective evolutionary algorithm in the field of air combat mission planning. The specific tasks include the positioning of air strike dynamic targets, intelligence surveillance and reconnaissance (ISR) mission planning. The experiences and lessons from these studies are summarized and the possible future development direction is discussed.

关 键 词：多目标进化算法 任务规划 空中作战 

分 类 号：N945[自然科学总论—系统科学]