论文:2014,Vol:32,Issue(4):563-568
引用本文:
李浩宇, 吕梅柏. 一种基于改进的蚁群优化算法的三维空间路径搜索算法[J]. 西北工业大学
Li Haoyu, L�Meibo. A Three Dimensional Route Planning Method Based on Improved Ant Colony Optimization Algorithm[J]. Northwestern polytechnical university

一种基于改进的蚁群优化算法的三维空间路径搜索算法
李浩宇, 吕梅柏
西北工业大学 航天学院, 陕西 西安 710072
摘要:
针对传统二维平面的随机搜索算法——蚁群优化算法不能满足三维空间路径搜索以及快速性要求等问题,提出了改进的方法。基于栅格离散方法创建空间环境地图,通过引入搜索主方向、可视域及可行域等定义将搜索算法扩展至三维空间,建立了三维空间下的蚁群优化算模型,并给出该方法的搜索流程。而后根据此模型及流程实现了仿真程序,得到仿真结果,并与传统方法做出了分析比较,得出该改进方法具有较快的收敛速度、较好的稳定性和更高的计算效率。
关键词:    蚁群优化算    栅格法    三维搜索   
A Three Dimensional Route Planning Method Based on Improved Ant Colony Optimization Algorithm
Li Haoyu, L�Meibo
School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China
Abstract:
In this paper, we proposed a new method to improve the performance of Ant Colony Optimization (ACO) algorithm used in route planning. Concerning the unavailable and in-efficient shortages of ACO when used in three-dimension situations, a modified model, which uses new definitions of marching direction, visible domains and reachable domains, utilizes Grid Representation Method for mapping, is introduced in this paper. Then a pro-cedure is given on this model. At last simulation implementation in MATLAB code is used for verifying this method and the results are shown in diagram forms. Compared with conventional method, the results and their analysis show preliminary the modified method has a rapid convergence rate and strong robustness and higher computing efficien-cy.
Key words:    computational efficiency    convergence of numerical methods    evolutionary algorithms    flowcharting    iterative methods    MATLAB    probability    robustness (control systems)     schematic diagrams    three dimensional    ant colony optimization (ACO)    grid representation method    three-dimensional search   
收稿日期: 2013-12-28     修回日期:
DOI:
基金项目: 国家自然科学基金(61174204)资助
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作者简介: 李浩宇(1990-),西北工业大学硕士研究生,主要从事导航制导与控制的研究。
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