基于混合量子算法的武器目标分配研究
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摘要
目前,虽已出现许多针对火力对抗武器目标分配问题的新型算法设计,然而由于问题的NP-hard特性及算法依据不同环境的较强针对性,在大规模来袭目标情况下,对多属性武器的选择决策仍显低效。为了进一步降低火力对抗中武器损耗并提高目标打击力度,分析并建立了武器目标分配模型,并针对该模型设计了新型混合量子算法,使得NP-hard武器目标分配问题的求解更高效。
Although many researches have been focused on the Weapon Target Assignment( WTA) problem,the decision efficiency are still to be improved. That is mainly because it is NP-hard and many existing algorithms have strong depend on the problem situation. When facing large scale aerial targets,decision on weapon assignment with different kinds of weapon characteristics is still inefficient. For further improving the target attack effectiveness and reduce the loss of weapons,the model of WTA is established with the consideration of different weapon characteristics and a new hybrid quantum-based step tuning algorithm is presented based on quantum coding and genetic algorithm for the decision of WTA. The analysis and performance of the new hybrid algorithm show its effectiveness and improvements in solving WTA problem.
Although many researches have been focused on the Weapon Target Assignment( WTA) problem,the decision efficiency are still to be improved. That is mainly because it is NP-hard and many existing algorithms have strong depend on the problem situation. When facing large scale aerial targets,decision on weapon assignment with different kinds of weapon characteristics is still inefficient. For further improving the target attack effectiveness and reduce the loss of weapons,the model of WTA is established with the consideration of different weapon characteristics and a new hybrid quantum-based step tuning algorithm is presented based on quantum coding and genetic algorithm for the decision of WTA. The analysis and performance of the new hybrid algorithm show its effectiveness and improvements in solving WTA problem.
引文
[1]蔡怀平,陈英武.武器-目标分配(WTA)问题研究进展[J].火力与指挥控制,2006,31(12):985-989.
[2]Lloyd S P,Witsenhausen H S.Weapons allocation is NPComplete[C].Proceedings of the 1986 Summer Conference on Simulation,1986:1054-1058.
[3]Adnan Y.The generalized weapon target assignment problem[C].The 10th International Command and Control Research and Technology symposium,2005:13-16.
[4]陈建虎,吕志明.武器-目标分配的模糊多目标规划[J].武器装备自动化,2007,26(6):3-4.
[5]廖沫,陈宗基.基于满意决策的多机协同目标分配算法[J].北京航空航天大学学报,2007,33(1):81-85.
[6]曹伟华,焦红革,魏建辉.遗传算法在武器目标分配中的应用[J].四川兵工学报,2008,(5):119-121.
[7]袁梅,凌明祥,曾庆双.基于信息素递减的蚁群算法的WTA问题求解[J].计算机仿真,2008,25(2):23-25.
[8]张海兵,徐诚,李世永.贪心遗传算法及其在武器目标分配问题中的应用[J].弹道学报,2007,19(2):40-43.
[9]许建中.基于遗传算法的武器目标分配模糊多目标规划[J].军事运筹与系统工程,2010,3:70-74.
[10]Han K H,Kim J H.Genetic quantum algorithm and its application to combinatorial optimization problem[C].Proceedings of the 2000 Congress on Evolutionary Computation,2000:1354-1360.
[11]Han K H,Kim J H.Quantum-inspired evolutionary algorithm for a class of combinatorial optimization[J].IEEE Transactions on Evolutionary Computing,2002,6(6):580-593.
[12]李士勇,李盼池.求解连续空间优化问题的量子粒子群算法[J].量子电子学报,2007,24(5):569-574.
[2]Lloyd S P,Witsenhausen H S.Weapons allocation is NPComplete[C].Proceedings of the 1986 Summer Conference on Simulation,1986:1054-1058.
[3]Adnan Y.The generalized weapon target assignment problem[C].The 10th International Command and Control Research and Technology symposium,2005:13-16.
[4]陈建虎,吕志明.武器-目标分配的模糊多目标规划[J].武器装备自动化,2007,26(6):3-4.
[5]廖沫,陈宗基.基于满意决策的多机协同目标分配算法[J].北京航空航天大学学报,2007,33(1):81-85.
[6]曹伟华,焦红革,魏建辉.遗传算法在武器目标分配中的应用[J].四川兵工学报,2008,(5):119-121.
[7]袁梅,凌明祥,曾庆双.基于信息素递减的蚁群算法的WTA问题求解[J].计算机仿真,2008,25(2):23-25.
[8]张海兵,徐诚,李世永.贪心遗传算法及其在武器目标分配问题中的应用[J].弹道学报,2007,19(2):40-43.
[9]许建中.基于遗传算法的武器目标分配模糊多目标规划[J].军事运筹与系统工程,2010,3:70-74.
[10]Han K H,Kim J H.Genetic quantum algorithm and its application to combinatorial optimization problem[C].Proceedings of the 2000 Congress on Evolutionary Computation,2000:1354-1360.
[11]Han K H,Kim J H.Quantum-inspired evolutionary algorithm for a class of combinatorial optimization[J].IEEE Transactions on Evolutionary Computing,2002,6(6):580-593.
[12]李士勇,李盼池.求解连续空间优化问题的量子粒子群算法[J].量子电子学报,2007,24(5):569-574.