|本期目录/Table of Contents|

[1]邱晨,周海峰,王荣杰,等.改进蚁群算法的无人救生船航迹规划[J].集美大学学报(自然科学版),2019,24(5):358-363.
　QIU Chen,ZHOU Haifeng,WANG RongjieLIN Zhonghua.Track Planning of Unmanned Lifeboat Based on Improved Ant Colony Algorithm[J].Journal of Jimei University,2019,24(5):358-363.
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《集美大学学报（自然科学版）》[ISSN:1007-7405/CN:35-1186/N]

卷:
第24卷
期数:
2019年第5期
页码:
358-363
栏目:
航海技术与物流工程
出版日期:
2019-09-28

文章信息/Info

Title:
Track Planning of Unmanned Lifeboat Based on Improved Ant Colony Algorithm
作者:
邱晨1; 2; 周海峰1; 2; 王荣杰1; 2; 林忠华3
(1.集美大学轮机工程学院,福建 厦门 361021 ;2.福建省船舶与海洋工程重点实验室,福建 厦门 361021 ;3.集美大学机械与能源工程学院,福建 厦门 361021)
Author(s):
QIU Chen1; 2; ZHOU Haifeng1; 2; WANG Rongjie1; 2LIN Zhonghua3
(1.School of Marine Engineering,Jimei University,Xiamen 361021,China 2.Key Laboratory of Naval Architecture and Ocean Marine Engineering of Fujian Province,Xiamen 361021,China 3.School of Mechanical and Energy EngineeringJimei University,Xiamen 361021,China)
关键词:
蚁群算法; 时间; 无人救生船; 航迹规划
Keywords:
ant colony algorithm; time; unmanned lifeboat; track planning
分类号:
-
DOI:
-
文献标志码:
-
摘要:
为了缩短无人救生船从出发点到险情发生点所需时间，需要规划一条无碰撞的安全航行路径。针对当前路径规划中存在的问题，提出一种考虑时间优化的改进蚁群算法，将该算法应用于无人救生船航迹优化，建立了无人船在航行过程中的时间模型，得到无人救生船航行路径的时耗计算公式，改变了信息素更新方式。仿真结果表明，与传统蚁群算法相比，改进后的算法能有效降低航行时间。
Abstract:
The time required for an unmanned lifeboat from the point of departure to the point of occurrence of the danger is one of the important factors for the successful completion of a rescue mission.Aiming at the problem that the current path planning mainly focuses on the length of the path rather than the length of time,an improved ant colony algorithm factoring time optimization is proposed for the track optimization of unmanned lifeboats.The time model of the unmanned ship sailing process is established,and the time consumption calculation formula of the unmanned ship ’s navigation path is obtained.An improved ant colony algorithm for time optimization is proposed to change the pheromone update mode.The simulation results show that the improved algorithm can effectively reduce the navigation time compared with the traditional ant colony algorithm.

参考文献/References:

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备注/Memo

备注/Memo:
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更新日期/Last Update: 2019-11-04