系统工程与电子技术

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基于子目标进化算法的要地防空武器系统优化部署

雷宇曜, 姜文志, 刘立佳, 刘涛   

  1. 海军航空工程学院兵器科学与技术系, 山东 烟台 26400
  • 出版日期:2016-01-30 发布日期:2010-01-03

Weapon system deployment optimization based on a sub-objective evolutionary algorithm for key point air defense

LEI Yu-yao, JIANG Wen-zhi, LIU Li-jia, LIU Tao   

  1. Department of Ordnance Science and Technology, Naval Aeronautical and Astronautical University, Yantai 264001, China
  • Online:2016-01-30 Published:2010-01-03

摘要:

针对现代空袭、防空特点,提出要地防空远程扇形,中程、近程环形的部署方案。根据距要地不同距离范围空袭目标的特点和各型武器的性能,对部署范围进行划分。建立考虑均匀性、纵深性、靠前部署、相互掩护以及接力制导目标的高维多目标优化函数模型。从缩小搜索空间入手,在理论上证明了通过子目标函数值排序进行Pareto最优解求取的可行性,提出了子目标进化算法。同目前的高维多目标优化问题求解算法相比,显示出一定的优势。通过一个具体的部署算例,验证了所提出算法和建立的高维多目标优化模型的正确性和可行性。

Abstract:

Based on the characteristic of modern air attack and air defense, a model that near and medium distance is ringshaped deployment and fan shaped deployment which is far from the key point is established.Because of different distance from the keypoint, there are different air attack targets.The deployment area is divided into three layers.Considering the fire equality, fire depth, fringe deployment, covering network, and relay guidance factors, a highdimensional objectives function for airdefense weapon system deployment is built.By sorting the value of the sub-objective function, the searching steps are reduced.Then, a sub-objective evolutionary algorithm (SOEA) is put forward and the theoretical feasibility is proved.The performance of the SOEA is better than other high dimensional objectives optimization algorithms.The simulation results of a deployment example show that the SOEA and the high dimensional objectives model is correct and feasible.