Majorization Of Artillery Fire Distribution Base On Quantum Genetic Algorithm

摘要：

Artillery fire Distribution is a typical NP-hard problem, it will fall into the plight of local optimum when we use traditional methods to solve the problem. The idea of qubit and quantum gate are introduced to QGA(quantum genetic Algorithm ),which combine quantum computing with genetic algorithms and it possesses those characters such as higher velocity of convergence and better optimization seeking compared with traditional evolution algorithm. This thesis solve the problem of artillery fire distribution by QGA and It has been proved this method is more effective than traditional GA(genetic algorithm) in solving optimization of Artillery fire distribution by simulation experiment.

关键词： GA QGA Artillery fire distribution Majorization

作者: Wang zhiteng Zhang hongjun Zhang rui Huang ying Shan li li Xing ying

作者单位: PLA University science and technology ,Nanjing, 210007,China

会议类型: 国际会议

会议名称: 2012 International Conference on Intelligent System Design and Engineering Applications(2012年智能系统设计与工程应用国际会议 ISDEA 2012)

会议地点: 三亚

会议语种:英文

页码: 337-340

在线出版日期: 2012-01-06（万方平台首次上网日期，不代表论文的发表时间）