基于GA-PSO的天基预警系统资源调度方法  

Resource Scheduling Method for Space-Based Early Warning System Based on GA-PSO Algorithm

作　　者：张辰璐 彭冬亮[1] 方韬[1] 谷雨[1] 

机构地区：[1]杭州电子科技大学通信信息传输与融合技术国防重点学科实验室,浙江杭州310018

出　　处：《信息与控制》2016年第2期199-203,210,共6页Information and Control

基　　金：国家自然科学基金项目资助项目(61174024);国家重点基础研究发展计划资助项目(2012CB821200)

摘　　要：为解决天基预警系统中的卫星资源调度问题,从预警任务特点出发,在对预警任务进行分解的基础上,建立了资源调度模型.结合传统遗传算法(GA)和粒子群算法(PSO)的优点,采用一种混合遗传粒子群(GA-PSO)算法来求解资源调度问题.该算法在解决粒子编解码问题的前提下,将遗传算法的遗传算子应用于粒子群算法,改善了粒子群算法的寻优能力.实验结果表明,提出的算法能有效解决多目标探测时天基预警系统的资源调度问题,调度结果优于传统粒子群算法和遗传算法.To solve the resource scheduling problem of satellites in space-based early warning system,we build a resource scheduling model based on the characteristics of the early warning tasks and their decomposition. We propose a hybrid GA-PSO optimization algorithm,which combines the advantages of genetic algorithm（ GA）and particle swarm optimization（ PSO）,to solve the resource scheduling problem for the space-based early warning system. The algorithm introduces the genetic operators of GA into PSO algorithm to improve the search ability of PSO algorithm,while solving the problem of particles coding and decoding. The experimental results demonstrate that the proposed algorithm can solve resource scheduling problem of space-based early warning system for multi-target detection effectively and space-based early warning missions,and the scheduling results is better than GA and PSO.

关 键 词：天基预警 资源调度 遗传算法 粒子群算法 多目标探测 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]