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改进蚁群算法及其在船舶最优航线导航中的应用 预览

An improved ant colony algorithm and its application in ship optimal route navigation
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摘要 由于海洋航行环境复杂,同时受到各种风、浪、流等多种因素的影响,使得在通航水域发生的安全事故随之增加,造成巨大的财产损失,同时危及船员的生命安全。为了保障船舶在海洋上安全高速航行,必须设计出最为安全可靠的最优航线。针对传统的蚁群算法在船舶最优航线导航过程中后期存在收敛速度慢、易出现停滞的缺陷,设计一种改进的蚁群算法进行船舶最优航线导航。首先利用混合更新策略,对船舶航线栅格上的信息素进行更新,然后在找到的船舶的所有可行航线中,搜索出最优航线,最后进行仿真测试。实验结果表明,相比较于对比算法,改进蚁群算法搜索到的航线更优,更为安全可靠,所耗费的时间少于对比算法,是一种效率高、可靠性好的船舶最优航线导航算法。 Because of the complex marine navigation environment and the influence of various wind, wave, current and other factors, the number of safety accidents in navigable waters increases, resulting in huge property losses and endangering the lives of crew. In order to ensure the safe and high-speed navigation of ships on the sea, it is necessary to design the most safe and reliable optimal route. Aiming at the shortcomings of slow convergence speed and easy stagnation of traditional ant colony algorithm in the later stage of ship optimal route navigation, an improved ant colony algorithm is designed for ship optimal route navigation. Firstly, the pheromone on ship route grid is updated by using hybrid update strategy, and then the optimal route is searched out in all feasible routes of ships found. Finally, the simulation test shows that the improved ant colony algorithm is more secure and reliable than the contrast algorithm, and it takes less time than the contrast algorithm. It is an efficient and reliable optimal navigation algorithm for ships.
作者 杨海 YANG Hai(College of Information Science and Electricity Engineering,Shandong Jiaotong University,Jinan 250357,China)
出处 《舰船科学技术》 北大核心 2019年第4期25-27,共3页 Ship Science and Technology
关键词 最优航线导航 蚁群算法 改进蚁群算法 船舶 optimal route navigation ant colony algorithm improved ant colony algorithm ship
作者简介 杨海(1980–),男,硕士,副教授,研究方向为计算机算法、生物信息学及智能交通等。
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