集装箱码头泊位系统资源配置与调度优化研究

发布时间：2018-11-14 16:48

【摘要】：集装箱运输的快速发展对集装箱码头的作业效率要求越来越高。在集装箱码头中与作业效率相关的泊位一直是稀缺资源,岸桥则是进行装卸的主要设备。泊位与岸桥资源的合理利用,能够有效的缩短船舶在港时间,提高码头的服务质量,实现港口效益的最大化。本文在归纳和评述大量相关文献的基础上,针对当前泊位、岸桥调度问题的研究现状,发现目前该问题研究仍不够理想。泊位与岸桥联合调度研究需要进一步改善,基于泊位、岸桥的主辅码头靠泊决策协同优化问题更是缺乏研究。本文针对上述几方面的问题,做出如下研究工作： (1)考虑集装箱码头现实约束,根据泊位资源动态配置的具体特征,利用排队论的相关知识建立泊位资源动态配置模型,通过模拟迭代算法实现求解过程,实现泊位资源的动态配置。算例的实验结果证明该模型适合码头作业,具有良好的适应性。 (2)基于泊位资源动态配置的泊位计划,实现泊位与岸桥联合调度优化,构建联合调度模型,并通过遗传算法进行求解。在算例分析中,将联合调度优化的结果与单独优化的结果进行对比,无论是作业效率还是空闲率,联合优化的结果具有高效性,模型和算法具有高效性。 (3)基于泊位资源动态配置、泊位与岸桥的联合调度优化,构建主辅码头靠泊决策协同优化模型,在算法设计上,对遗传算法进行改进。通过编程和仿真实验,得出主辅码头靠泊决策以及转运计划,并通过对三种不同情形下的求解结果对比,算法能在较短的时间内收敛,证明了算法的有效性。
[Abstract]:With the rapid development of container transportation, the operational efficiency of container terminal is becoming more and more high. Berths related to operational efficiency in container terminals are always scarce resources, and quayside bridges are the main equipment for loading and unloading. The reasonable utilization of berth and shore bridge resources can effectively shorten the ship's time in port, improve the service quality of wharf, and realize the maximization of port benefit. On the basis of summarizing and reviewing a large number of related literatures, this paper finds that the current research on berth and quayside bridge scheduling problem is still not satisfactory. The research on joint dispatch of berth and quayside bridge needs further improvement. Based on berth, the cooperative optimization of berthing decision for main and auxiliary wharves is even less studied. In view of the above problems, this paper makes the following research work: (1) considering the practical constraints of container terminal, according to the specific characteristics of the dynamic allocation of berth resources, The dynamic allocation model of berth resources is established by using the relevant knowledge of queuing theory, and the dynamic allocation of berth resources is realized by simulating iterative algorithm. The experimental results show that the model is suitable for wharf operation and has good adaptability. (2) based on the berth plan of dynamic allocation of berth resources, the joint scheduling optimization of berth and quayside bridge is realized, and the joint scheduling model is constructed and solved by genetic algorithm. In the case study, the results of joint scheduling optimization are compared with those of single optimization. The results of joint optimization are efficient, and the model and algorithm are efficient, regardless of job efficiency or idle rate. (3) based on the dynamic allocation of berth resources and the joint scheduling optimization of berth and shore bridge, the cooperative optimization model of berthing decision for main and auxiliary wharves is constructed, and the genetic algorithm is improved in algorithm design. Through programming and simulation experiments, the berthing decision and transportation plan of the main and auxiliary wharf are obtained. By comparing the results of three different cases, the algorithm can converge in a short time, which proves the validity of the algorithm.
【学位授予单位】：大连海事大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：U656.135;U691

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