Adaptive optimization of agile organization of command and control resource  

作　　者：Yang Chunhui Liu Junxian Chen Honghui Luo Xueshan 

机构地区：[1]Dept. of Management, Naval Univ. of Engineering, Wuhan 430033, P. R. China [2]Key Lab. of C^4ISR, National Univ. of Defense Technology, Changsha 410073, P. R. China

出　　处：《Journal of Systems Engineering and Electronics》2009年第3期558-564,共7页系统工程与电子技术（英文版）

摘　　要：Adaptive optimization is one of the means that agile organization of command and control resource （AOC2R） adapts for the dynamic battlefield environment. A math model of the adaptive optimization of AOC2R is put forward by analyzing the interrelating concept and research. The model takes the adaptive process as a multi-stage decision making problem. The 2-phases method is presented to calculate the model, which obtains the related parameters by running the colored Petri net （CPN） model of AOC2R and then searches for the result by ant colony optimization （ACO） algorithm integrated with genetic optimization techniques. The simulation results demonstrate that the proposed algorithm greatly improves the performance of AOC2R.Adaptive optimization is one of the means that agile organization of command and control resource （AOC2R） adapts for the dynamic battlefield environment. A math model of the adaptive optimization of AOC2R is put forward by analyzing the interrelating concept and research. The model takes the adaptive process as a multi-stage decision making problem. The 2-phases method is presented to calculate the model, which obtains the related parameters by running the colored Petri net （CPN） model of AOC2R and then searches for the result by ant colony optimization （ACO） algorithm integrated with genetic optimization techniques. The simulation results demonstrate that the proposed algorithm greatly improves the performance of AOC2R.

关 键 词：command and control organization adaptive optimization of organization dynamic-window-search ant colony optimization 3-phase organizational design. 

分 类 号：TP312[自动化与计算机技术—计算机软件与理论] V212.13[自动化与计算机技术—计算机科学与技术]