摘要
保证对区域目标的覆盖率、重叠率以及部署平台数量的均衡是浮空平台对区域覆盖部署的重要工作。提出基于遗传算法的浮空平台部署规划算法,使用变长染色体对方案进行编码;采用启发式与随机生成两种方法构造初始种群,既考虑到平台分布性又考虑到种群多样性,使算法能尽快搜索出优化解;根据应用需要设置合理的加权系数,采用平方加权法设计方案评价函数;设计了动态插入、删除算子,使搜索过程中自动根据方案效果进行动态调整。仿真实验表明,该算法能在较短时间内求得满足要求的部署方案,提高了浮空平台对区域覆盖规划的效率。
The area-coverage deployment of aerostat platforms is to ensure the coverage rate,overlapping rate and the balance of platform amount.A platform deployment algorithm based on genetic algorithm was proposed,in which the variable-length chromosomes were used to encode the program,and both the heuristics and randomly generated methods used for constructing the initial population.Both platform distribution and the diversity of population were taken into consideration,so that the algorithm can search out the optimum solution as quickly as possible.A reasonable weighting factor was set up depending on the application needs,and squared weighting method was used to design the evaluation function.A dynamic insert/delete operator was used,thus adjustment could be made automatically according to the program effectiveness during searching.Simulation results showed that this algorithm can obtain a program in a relatively short period of time,which meets the requirements of the deployment and improves the efficiency of the platform deploying planning.
出处
《电光与控制》
北大核心
2010年第11期9-12,共4页
Electronics Optics & Control
基金
"八六三"项目基金资助(2006AA701117)
关键词
浮空平台
区域覆盖
遗传算法
多目标优化
aerostat platform
area coverage
genetic algorithm
multi-objective optimization
