Ship Route Planning Based on Particle Swarm Optimization

Yu Shen, Fuping Wang, Peimin Zhao, Xinchi Tong, Jinhui Huang, Kai Chen, Huajun Zhang
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引用次数: 4

Abstract

The ship route planning has two problems to solve. The first problem is how to model the environment of the navigation area, and the second one is how to use an optimal algorithm to search the global optimal route. This paper combines the particle swarm optimization (PSO) algorithm with the tangent graph method to search the optimal ship route. At first, it uses the tangent graph method to obtain the static obstacle information and establishes the static environment model of the navigation area. It designs a cost function evaluating the total distance from the start point to the terminal point. The PSO algorithm takes the minimum value of the cost function as its target to search the global shortest route. Based on the environment model, the PSO individuals are outside of the obstacle hull area, and the optimal results are feasible solutions satisfying the requirement. It designs the detail optimization operations according to the PSO principal. The results show that the proposed route planning method is effective to get the shortest route.
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基于粒子群算法的船舶航路规划
船舶航路规划有两个问题需要解决。第一个问题是如何对导航区域的环境进行建模,第二个问题是如何使用最优算法来搜索全局最优路线。本文将粒子群优化算法与切线图法相结合,进行船舶最优航路的搜索。首先,采用切线图法获取静态障碍物信息,建立导航区域的静态环境模型;它设计了一个代价函数来计算从起点到终点的总距离。PSO算法以代价函数的最小值为目标,搜索全局最短路由。基于环境模型,粒子群个体处于障壳区域外,最优结果为满足要求的可行解。根据粒子群原理设计了具体的优化操作。结果表明,所提出的路线规划方法能够有效地获得最短的路线。
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