船舶物流路径规划的数学模型构建及求解
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摘要
船舶物流路径规划的研究具有十分重要的经济价值,当前船舶物流路径规划方法无法找到最优的船舶物流路径规划方案,使得船舶物流运输的成本过高,为此本文设计了基于蚁群算法和粒子群算法的船舶物流路径规划方法。首先分析船舶物流路径规划研究的历史,建立船舶物流路径规划的数学模型,然后采用粒子群算法对船舶物流路径规划的数学模型进行求解,找到有效的船舶物流路径规划方案集合,并在此基础上采用蚁群算法对船舶物流路径规划方案集合进行搜索,找到最优的船舶物流路径规划方案,最后与单一蚁群算法、粒子群算法进行了船舶物流路径规划问题求解的仿真实验。本文方法避免了单一蚁群算法、粒子群算法求解速度慢,难以找到最优船舶物流路径规划方案不足,得到的船舶物流路径规划方案可以帮助企业节约物流运输成本。
The research of ship logistics path planning has very important economic value. The current method of ship logistics path planning can not find the optimal plan of ship logistics path planning, which makes the cost of ship logistics transportation too high. Therefore, this paper designs a method of ship logistics path planning based on ant colony algorithm and particle swarm optimization. Firstly, the history of the research on ship logistics path planning is analyzed, and the mathematical model of ship logistics path planning is established. Then, the mathematical model of ship logistics path planning is solved by particle swarm optimization algorithm, and an effective set of ship logistics path planning schemes is found. On this basis, the ant colony algorithm is used for ship Logistics path planning. The set of planning schemes is searched to find the optimal ship logistics path planning scheme. Finally, the simulation experiment of solving ship logistics path planning problem is carried out with single ant colony algorithm and particle swarm optimization algorithm. This method avoids the slow speed of solving single ant colony algorithm and particle swarm optimization algorithm, and it is difficult to find the optimal ship logistics path. The path planning scheme is inadequate, and the obtained ship logistics path planning scheme can help enterprises save logistics transportation costs.
The research of ship logistics path planning has very important economic value. The current method of ship logistics path planning can not find the optimal plan of ship logistics path planning, which makes the cost of ship logistics transportation too high. Therefore, this paper designs a method of ship logistics path planning based on ant colony algorithm and particle swarm optimization. Firstly, the history of the research on ship logistics path planning is analyzed, and the mathematical model of ship logistics path planning is established. Then, the mathematical model of ship logistics path planning is solved by particle swarm optimization algorithm, and an effective set of ship logistics path planning schemes is found. On this basis, the ant colony algorithm is used for ship Logistics path planning. The set of planning schemes is searched to find the optimal ship logistics path planning scheme. Finally, the simulation experiment of solving ship logistics path planning problem is carried out with single ant colony algorithm and particle swarm optimization algorithm. This method avoids the slow speed of solving single ant colony algorithm and particle swarm optimization algorithm, and it is difficult to find the optimal ship logistics path. The path planning scheme is inadequate, and the obtained ship logistics path planning scheme can help enterprises save logistics transportation costs.
引文
[1]苏明.广东港口物流企业发展路径探究--基于“海上丝绸之路”倡议[J].北方经贸,2018,14(8):15-17.
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[5]邓必年.基于蚁群优化算法的物流配送路径研究[J].现代电子技术,2017,40(15):167-170.
[2]潘国强,胡俊逸,洪敏.考虑GIS的物流配送区域划分与路径规划算法[J].大连海事大学学报,2015,41(1):83-90.
[3]李耀庭,刘怡君,蔡维晓,等.基于改进Dijkstra算法的应急物流路径规划[J].军事交通学院学报,2018,20(7):54-58.
[4]王旭升,尤小霞.基于混合遗传优化算法的物流配送路径分析[J].物流技术,2014,33(5):269-271.
[5]邓必年.基于蚁群优化算法的物流配送路径研究[J].现代电子技术,2017,40(15):167-170.