集装箱码头箱位分配与装船顺序研究

发布时间：2018-11-20 11:39

【摘要】：随着集装箱船舶运输的快速发展，合理解决港口堆场集装箱的箱位分配与集装箱装船顺序，减少堆场的翻箱率，从而提高堆场的工作效率，是所有船舶公司和港口码头都面临的一个重要课题．码头出口集装箱的箱位分配是将出口集装箱按照一定的堆场规则，有序的在堆场中进行堆放．装船顺序是集装箱船舶运输的一个核心环节，在装船过程中，要尽可能减少堆场集装箱装载时的翻箱率以及集装箱卸载时的翻箱率，并形成集装箱在船舶上的装载位置及装船先后顺序．箱位分配与装船顺序问题直接影响着船舶的行驶安全和堆场机械作业效率，研究码头出口集装箱的箱位分配与装船顺序问题，对于集装箱船舶运输都有着十分重要意义．随着现代控制理论、优化方法、人工智能等迅速发展，各种智能算法如遗传算法（GA）、神经网络（ANNs）、蚁群算法（ACO）、粒子群算法（PSO）等相继提出，为解决场出口集装箱的箱位分配，合理安排装船顺序，提供了新的解决思路，，使集装箱船舶配载利用计算机系统进行科学的管理成为可能．本文以某港口s为例，结合粒子群算法，对出口集装箱的箱位分配，以及集装箱的装船顺序进行了初步探讨与研究，主要工作如下： 1.考虑集装箱的重量及目的港，以航程信息和堆场摆放规则为约束，以出口集装箱的装船路径和堆区的翻箱率为目标，建立适合出口集装箱堆场的箱位分配模型.利用粒子群算法对模型求解，数据实验表明该模型能够减少堆场翻箱率，提高堆场机械的作业效率，具有一定的实用性. 2.针对码头作业和集装箱船舶的复杂性，在堆场任意两个集装箱相对位置的基础上，给出它们之间的翻箱关系，以堆场上总的装载集装箱为约束，考虑集装箱重量、装船顺序和它们在船舶上的装载位置，以船舶稳性为目标，建立了新的装船顺序整数规划模型．结合利用粒子群算法，并构造出针对于模型的装船顺序求解算法，通过数据实验仿真，可以得出模型的可行性和算法的有效性与实用性． 3.分析了船舶稳性与堆场集装箱翻箱率的关系，在已知集装箱的重量、航程等信息的基础上，把出口集装箱的箱位分配与装船顺序综合一起进行考虑分析，建立以堆场翻箱率、船舶卸载翻箱率及船舶稳性为目标的多目标规划模型，并运用粒子群算法对模型进行求解，并利用Matlab仿真证明了模型的合理性．
[Abstract]:With the rapid development of container shipping, the distribution of container space and the sequence of container loading in port yard are reasonably solved, and the turnover rate of container yard is reduced, so as to improve the working efficiency of yard. It is an important subject that all shipping companies and port terminals are facing. The allocation of container spaces for export containers at the terminals is to follow certain yard rules for export containers. The sequence of loading is a core link of container shipping. During loading, we should reduce the rate of turning over the container during loading and unloading the container as much as possible. The position and sequence of container loading on the ship are formed. The distribution of the container position and the sequence of loading have a direct impact on the safety of the ship and the efficiency of the yard machinery operation. It is very important for container shipping to study the distribution of container space and the loading sequence of container at the exit of wharf. With the rapid development of modern control theory, optimization method, artificial intelligence and so on, A variety of intelligent algorithms, such as genetic algorithm (GA), neural network, (ANNs), ant colony algorithm, (ACO), particle swarm optimization algorithm (PSO) and so on, have been put forward one after another. A new solution is provided, which makes it possible for container ship stowage to be managed scientifically by computer system. In this paper, a port s is taken as an example, and particle swarm optimization algorithm is used to allocate the container space of export container. And the shipping sequence of containers is discussed and studied. The main work is as follows: 1. Considering the weight and destination port of containers, taking voyage information and yard layout rules as constraints, and taking the loading path of export containers and the turnover rate of stacking areas as the targets, a container allocation model suitable for export container yard is established. Particle swarm optimization (PSO) algorithm is used to solve the model. The experimental results show that the model can reduce the turnover rate of the yard and improve the working efficiency of the yard machinery. 2. In view of the complexity of terminal operation and container ship, on the basis of the relative position of any two containers in the yard, the relationship between them is given. Taking the total loading container on the yard as the constraint, the container weight is considered. In this paper, a new integer programming model of ship loading sequence is established with the object of ship stability and their loading position on the ship. A new algorithm for solving the loading order is constructed by using particle swarm optimization algorithm. The feasibility of the model and the validity and practicability of the algorithm can be obtained through the data experiment and simulation. 3. The relationship between ship stability and container turnover rate in yard is analyzed. On the basis of known information of container weight and voyage, the distribution of container position of export container and the sequence of loading are considered and analyzed synthetically, and the turnover rate of container yard is established. The multi-objective programming model with ship unloading rate and ship stability as the target is solved by particle swarm optimization. The rationality of the model is proved by Matlab simulation.
【学位授予单位】：鲁东大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：U695.22

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