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基于人工智能技术的船舶最优停靠点推荐研究
Research on recommendation of ship optimal docking point based on artificial intelligence technology
- DOI:
- 作者:
- 任冬炎1,2
REN Dong-yan1,2
- 作者单位:
- 1. 广西船联网工程技术研究中心，广西 南宁 530007;
2. 广西职业师范学院 计算机与信息工程学院，广西 南宁 530007
1. Guangxi Ship Networking Engineering Technology Research Center, Nanning 530007, China;
2. College of Computer and Information Engineering, Guangxi Vocational Normal University, Nanning 530007, China
- 关键词:
- 粒子群;泊位调度;流量;寻优
particle swarm;berth scheduling;flow rate;search for optimization
- 摘要:
- 大型运输船的航线规划中，选择恰当的港口停靠是一项重要内容。一方面，为了满足船载商品的物流运输需求，船舶需要在港口的泊位停泊；另一方面，受限于港口船舶的交通流量情况、泊位是否空闲、停靠时间等多种因素，船舶停靠点的需求直接决定了船舶航行的距离，也决定了船舶的运营成本。因此，进行船舶停靠港口的寻优成为一项热点研究。本文首先介绍了港口内泊位调度的理论基础，然后结合改进粒子群算法，建立一种船舶停靠点的寻优模型，并基于该模型实现了船舶的停靠点寻优，有重要的实际应用价值。
In the route planning of large commercial transport ships, choosing the right port call is an important content. On the one hand, in order to meet the needs of logistics transportation of goods on board, ships need to berth in the port. On the other hand, due to the traffic flow of ships in port, berth availability, docking time and other factors, the demand of ship docking point directly determines the sailing distance of ships, as well as the operating cost of ships. Therefore, optimizing the port of call has become a hot research. This paper first introduces the theoretical basis of berth scheduling in the port, and then combines the improved particle swarm optimization algorithm to establish a ship docking point optimization model, and realizes the ship docking point optimization based on this model, which has important practical application value.
2023,45(4): 155-158 收稿日期：2022-08-29
DOI：10.3404/j.issn.1672-7649.2023.04.031
分类号：U644.58
作者简介：任冬炎(1982-),女,硕士,讲师,主要从事人工智能及大数据研究
