基于协同memetic PSO算法的传感器目标分配问题求解

传感器目标分配问题是防空系统传感器管理的一项重要研究内容。对面向跟踪的防空系统传感器目标分配问题进行了研究，结合主客观分配原则，利用0-1整数规划模型对问题进行了建模，约束主要考虑传感器的跟踪能力和目标的被执行跟踪容量。构造了一种协同memetic 粒子群优化(particle swarm optimization, PSO)算法，分别采用PSO算法和邻域搜索算法作为全局搜索和局部搜索。为了在粒子位置矢量中反映出传感器组合，根据问题设计了一种特殊的粒子编码方法。最后通过仿真实验验证了算法的合理性和有效性。

Solving sensor-target assignment problem based on cooperative memetic PSO algorithm

The sensor-target assignment is a key problem of sensor management in aerial defence system. The research on the tracking oriented sensor-target assignment problem in aerial defence system is done, and a 0-1 integer programming model for the problem is built up with subjective and objective assignment rules, the constrains mainly include the sensor tracking capability and target capacity of being tracked. A cooperative memetic particle swarm optimization(PSO) algorithm is constructed by the PSO algorithm and the neighbor search algorithm. In order to reflect the sensor combination in particle position vector, a special particle coding method is designed. Finally the experiments show that the proposed algorithm is feasible and effective.