基于双向搜索的改进蚁群算法的船舶路径规划  

Ship Route Planning Using Improved Ant Colony Algorithm with Bi⁃Directional Search Strategy

作　　者：白响恩[1] 江明哲 徐笑锋 孙丁一 BAI Xiang’en;JIANG Mingzhe;XU Xiaofeng;SUN Dingyi(Marine College,Shanghai Maritime University,Shanghai 201306,China;Information Engineering College,Shanghai Maritime University,Shanghai 201306,China)

机构地区：[1]上海海事大学商船学院,上海201306 [2]上海海事大学信息工程学院,上海201306

出　　处：《中国航海》2022年第3期13-20,共8页Navigation of China

基　　金：国家自然科学基金面上项目“海陆统筹背景下航运产业可持续发展机制研究”(42176217);上海高水平地方高校创新团队(海事安全与保障)项目。

摘　　要：为解决船舶在较复杂水域的全局路径规划以及路径平滑问题,提出一种以传统的蚁群算法(Ant Colony Optimization,ACO)为基础,加入双向搜索算法解决传统ACO搜索时易陷入局部最优解的问题;对其拐点较多问题,引入转角函数ω来对路径进行平滑处理;利用双向A^(∗)算法来改进其在搜索过程中的方向性问题;根据信息素保留规律与迭代次数之间的规律对信息素挥发因数ρ进行改进。结果表明:改进的算法在收敛效果上要优于传统ACO和双向ACO,且改进的算法优化的路径更加平滑,拐点数目在简单环境中减少了46%,在复杂环境中减少了53%,在航海应用中具有实际意义。A mixture algorithm is used to perform ship route planning and smoothing for complex navigation waters.The algorithm is basically the Improved Ant Colony Algorithm with introduction of the bidirectional search algorithm to avoid being trapped in local optima.The turning angle functionωis introduced to smooth the generated route,so as to reduce the number of turning points.Bidirectional A star algorithm is used to improve the directivity in the search process.Pheromone evaporation coefficientρis improved according to the relevance of the number of iterations to pheromone retention.Experiments show that the method developed here converges faster than typical ant colony optimization and bidirectional ant colony optimization and generates smoother route,the number of turning points is 46%less for average navigation environment and 53%for complex navigation environment.

关 键 词：船舶路径规划 蚁群算法 转角函数ω 路径平滑 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TP242[自动化与计算机技术—控制科学与工程]