摘要
将传统的传感器目标分配问题转化为了基于跟踪效能最大和传感器使用率最小的多目标优化模型。利用非劣分层遗传算法处理传感器目标分配多目标优化问题。非劣分层遗传算法通过对种群内的所有个体的多个目标函数进行非劣分层排序来度量个体的适应能力,通过遗传算法能够获取Pareto最优解集。仿真试验表明该方法能够获得满意效果。
The sensor-target assignment problem is transformed into a multi-objective optimization model ,which is based on maximum detection efficiency and minimum the used sensor resource .The non-dominated set ranking genetic algo-rithm（NSGA- Ⅱ ） is presented to solve the multi-objective optimization sensor-target assignment problem .The population＇s fitness is evaluated by the non-dominated set rank ,the diversity evolution operation is evaluated by genetic algorithm （GA） . The proposed NSGA- Ⅱ algorithm can provide Pareto-optimal front .The simulation experiment gives good assignment re-sult .
出处
《舰船电子工程》
2016年第3期32-34,56,共4页
Ship Electronic Engineering
关键词
多目标优化
遗传算法
传感器目标分配
非劣分层
PARETO
集
multi-objective optimization
genetic algorithm
sensor-target assignment
non-dominated set ranking
Pa-reto set
作者简介
吴建刚，男，硕士，工程师，研究方向：项目管理。
