Particle Swarm Optimization Based on Genetic Operators for Sensor-Weapon-Target Assignment
In the modern battlefields based on network, guided weapons highly rely on the sensors, so the benefit of assigning a given weapon to a target often depends on the pre-assigned sensor. In order to solve sensorweapon-target (SWT) assignment which is an important activity involved in planning and executing a course of battle action, a model of SWT problem is established firstly. Secondly, particle swarm optimization based on genetic operators is put forward to solve the model, in which the restriction of problems is transformed by coding solutions, according to optimal solutions of population and individual, the new particle is updated by crossover, mutation and selection operators. Finally, after the numerical experiment of the algorithm, it is proved to be feasible and effective, especially in solving large-scale problems, it shows much better performance.
sensor-weapon-target assignment particle swarm optimization genetic operator
Huadong Chen Zhong Liu Yuelin Sun Yunfan Li
Electronics Eng. College, Naval Univ. of Engineering, Wuhan, Hubei Province, China Dept. of Basic Courses, Defense Information Academy, Wuhan, Hubei Province, China
国际会议
杭州
英文
748-751
2012-10-28（万方平台首次上网日期，不代表论文的发表时间）