基于遗传算法的点群选取模型技术  

Model of points selection in map using genetic algorithms

作　　者：武占峰[1] 吴裕树[1] 

机构地区：[1]北京理工大学计算机科学工程系,北京100081

出　　处：《计算机应用》2005年第3期654-656,共3页journal of Computer Applications

基　　金：国家部委预研项目

摘　　要：在地图上指定区域内依据一定的约束条件选取一组目标点 (称为点群 ),很多领域都会用到。结合点群目标选取的约束条件和遗传算法的基本原理与特点,设计了一种基于遗传算法的点群目标选取模型。考虑到要最大限度地保持点群的多样性、在内部各地段的分布密度等因素,使用一种家族内相关选择的方法,并提出非固定基因位交叉变异的改进策略。实际计算表明,该算法性能稳定、搜索效率高,节省时间和空间,能有效地避免算法的“早熟”现象,且快速找到全局最优解。Points selection in map is used in many fields. Combining the basic principle and characteristics of genetic algorithms with the basic principles of points selection, this paper designed a model of points selection in map based on genetic algorithms. In order to keep the variety of the points, and the internal distribution and density farthest, this paper proposed a new method with Elitist Recombination which employed an improved strategy of the ambulatory loca crossovers and mutations. Experimental results show that the method is timesaving and space-saving,it can avoid prematurity and quickly find optimal solution with stable performance and high search efficiency.

关 键 词：点群 遗传算法 交叉 变异 早熟 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]