期刊文献+

Solving algorithm for TA optimization model based on ACO-SA 被引量:4

Solving algorithm for TA optimization model based on ACO-SA
在线阅读 下载PDF
导出
摘要 An ant colony optimization (ACO)-simulated annealing (SA)-based algorithm is developed for the target assignment problem (TAP) in the air defense (AD) command and control (C2) system of surface to air missile (SAM) tactical unit. The accomplishment process of target assignment (TA) task is analyzed. A firing advantage degree (FAD) concept of fire unit (FU) intercepting targets is put forward and its evaluation model is established by using a linear weighted synthetic method. A TA optimization model is presented and its solving algorithms are designed respectively based on ACO and SA. A hybrid optimization strategy is presented and developed synthesizing the merits of ACO and SA. The simulation examples show that the model and algorithms can meet the solving requirement of TAP in AD combat. An ant colony optimization (ACO)-simulated annealing (SA)-based algorithm is developed for the target assignment problem (TAP) in the air defense (AD) command and control (C2) system of surface to air missile (SAM) tactical unit. The accomplishment process of target assignment (TA) task is analyzed. A firing advantage degree (FAD) concept of fire unit (FU) intercepting targets is put forward and its evaluation model is established by using a linear weighted synthetic method. A TA optimization model is presented and its solving algorithms are designed respectively based on ACO and SA. A hybrid optimization strategy is presented and developed synthesizing the merits of ACO and SA. The simulation examples show that the model and algorithms can meet the solving requirement of TAP in AD combat.
出处 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2011年第4期628-639,共12页 系统工程与电子技术(英文版)
基金 supported by the National Aviation Science Foundation of China(20090196002)
关键词 target assignment (TA) OPTIMIZATION ant colony optimization (ACO) algorithm simulated annealing (SA) algorithm hybrid optimization strategy. target assignment (TA), optimization, ant colony optimization (ACO) algorithm, simulated annealing (SA) algorithm,hybrid optimization strategy.
作者简介 Jun Wang was born in 1976. He is a Ph.D. and a lecturer in Air Force Engineering University. His research interests are effectiveness anal- ysis of complex weapon system, intelligent con- trol mechanism of air and space aerocraft, air defense C3I system. E-mail: wangjun197618@ 163.comXiaoguang Gao was born in 1958. She is a Ph.D., a professor and a doctorial tutor in Northwestern Polytechnical University. Her research interests are attack-defense confrontation simulation and combat effectiveness analysis of complex weapon system, aerospace vehicle control mechanism, autonomous control and mission planning for unmanned aerial vehicle, fire control theory of new concept weapon. E-mail: xggao @nwpu.edu.cnYongwen Zhu was born in 1978. He is a Ph.D. and a senior engineer in Equipment Academy of Air Force. His research interests are military operation research, air traffic control and aviation safety. E-mail: tianyiliang@tom.com
  • 相关文献

参考文献6

二级参考文献44

共引文献46

同被引文献87

引证文献4

二级引证文献64

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部