面向预警卫星调度问题的改进粒子群算法

An Improved Particle Swarm Optimization Algorithm for Early Warning Satellites Scheduling Problems

针对预警卫星调度问题的特点,提出了改进型粒子群算法。首先构建了粒子整数编码和解码机制,使粒子编码对应资源分配方案;其次,采用基于优先级的粒子群初始化机制,提高算法对可行解空间的遍历效率;其次对运算符进行重定义,解决基本粒子群算法无法处理离散变量优化问题。最后将改进的离散分群粒子群算法应用于预警任务—资源的调度问题中,实验结果表明,同其它算法相比,该算法具有较高求解性能。

Aim at the Characteristics of early warning satellites scheduling problems,a Improved Optimization Algorithm（IPSO） was proposed in the paper.Firstly,a particles code and decode mechanism of particle swarm was designed for IPSO Algorithm;Secondly,the paper introduced initialization mechanism based on priority for improving the searching efficiency of algorithm in feasible solution space;Thirdly,For PSO algorithm can not handle the discrete variable optimization problems,the improved algorithm introduced operator redefinition policy.Finally,the IGPSO algorithm was applied to early warning satellites scheduling problems.The experimental results show that,compared with other two algorithms,the method presented has better solving capacity in solving this kind of problem.