混堆集装箱码头场桥调度研究

发布时间：2018-07-25 06:49

【摘要】：随着经济全球化和世界一体化的发展,集装箱港口的节点作用越来越重要,集装箱码头的装卸效率、运作效率及效益引起越来越多的社会关注。在集装箱码头的日常运营中,集装箱堆场的效率对码头也比较重要。因此,集装箱码头堆场的设备资源和空间资源的管理及调度成为目前研究集装箱码头的热点之一。本论文以进出口集装箱混合堆存的码头为研究对象,以集卡等待时限及场桥间的干扰因素为约束,以智能化技术为手段,提出一个面向混堆集装箱码头堆场内的场桥调度及配置研究,以达到满足集卡时限情况下运作成本最小的目标。本文的主要研究内容如下：(1).在详细阅读有关集装箱码头堆场资源调度和配置的国内外文献的基础上,确定了论文的主要研究内容。其次,在详细分析了堆场作业系统、现实集装箱堆场管理及控制相关影响因素的基础上,界定了本文研究的具体问题。最后,确定了本文研究的面向混堆集装箱码头场桥调度的优化目标、实际约束、决策变量,进而形成了混堆集装箱码头场桥调度体系架构,作为后续各章决策模型的基础。(2).对混堆箱区(Zone)内单场桥调度进行了问题分析,提出了一个属于整数规划模型的单场桥调度模型,目标是最小化集卡等待产生的附加成本与场桥大车移动成本之和。接着,采用基于实数编码的遗传算法求解了该单场桥调度问题。(3).在(2)研究内容的基础上进一步深化,对混堆箱区(Zone)内多个场桥调度进行了问题分析,同样提出了一个多场桥调度整数规划数学模型,目标也是最小化集卡等待成本和场桥大车移动成本总和。然后,设计了一个改进的遗传算法用于求解模型,而且为了提高算法的全局寻优能力,采用新的变异操作、引入解空间切割方策略,并在算法框架中嵌入了基因修复技术。(4).创新性地对作业场桥数量不确定的多场桥调度问题进行了研究,即场桥配置调度集成优化研究。首先,对场桥配置＆调度集成优化进行了问题分析,提出了一个非线性优化数学模型,模型的目标是最小化任务等待成本、场桥非装卸成本。然后,结合模型的特点,设计一种结合禁忌搜索的遗传算法来进行优化求解。其中禁忌搜索的记忆功能被引进到变异操作,目的在于增强遗传算法的爬山能力。最后,基于实例验证了集成优化模型和提出算法的有效性。本文的研究成果有助于提高集装箱码头堆场的营运水平,尤其是为静态的混堆箱区内的场桥调度提供决策支持。同时对其他物流领域内大型设备的调度优化,具有理论上和方法上的借鉴意义。针对混堆集装箱码头场桥调度而开发的优化方法,对同类复杂系统优化问题的解决具有参考意义。研究中涉及集装箱码头的多目标营运,旨在解决其复杂性和实时性问题,对我国码头的实际生产具有一定的指导意义。
[Abstract]:With the development of economic globalization and the integration of the world, the node function of container port is becoming more and more important. The efficiency, operation efficiency and benefit of container terminal have attracted more and more attention. In the daily operation of container terminal, the efficiency of container yard is also important to the terminal. Therefore, the management and scheduling of equipment resources and space resources in container terminal yard has become one of the hotspots in the research of container terminal. In this paper, the wharf of mixed storage of import and export containers is taken as the research object, the waiting time of the collecting card and the interference factors between the field and bridge are taken as the constraints, and the intelligent technology is used as the means. This paper presents a study on the scheduling and configuration of the field bridge in the yard of the mixed reactor container terminal in order to achieve the goal of minimum operation cost under the condition of the time limit of the card collection. The main contents of this paper are as follows: (1). On the basis of detailed reading of domestic and foreign literatures on resource scheduling and allocation of container terminal yard, the main research contents of this paper are determined. Secondly, on the basis of the detailed analysis of the operation system of the yard, the management and control of the container yard, the paper defines the specific problems studied in this paper. Finally, the optimization objectives, practical constraints and decision variables of the hybrid stack container terminal yard bridge scheduling are determined in this paper, and the architecture of the hybrid container terminal yard bridge scheduling system is formed, which is the basis of the subsequent chapters of the decision-making model. (2). In this paper, the problem of single field bridge scheduling in (Zone) is analyzed, and a single field bridge scheduling model is proposed, which belongs to integer programming model. The goal is to minimize the sum of additional cost and moving cost. Then, genetic algorithm based on real number coding is used to solve the single field bridge scheduling problem. (3). (2) on the basis of further research, the problem of multi-field bridge scheduling in (Zone) is analyzed, and a mathematical model of integer programming for multi-field bridge scheduling is also proposed. The goal is also to minimize the sum of card wait cost and field bridge vehicle moving cost. Then, an improved genetic algorithm is designed to solve the model. In order to improve the ability of global optimization of the algorithm, a new mutation operation is adopted, and the strategy of dissecting space is introduced, and the gene repair technique is embedded in the framework of the algorithm. (4) The multi-field bridge scheduling problem with uncertain number of job yard bridges is studied innovatively, that is, the integrated optimization of field bridge configuration scheduling. Firstly, a nonlinear optimization mathematical model is proposed, which aims to minimize the task waiting cost and the non-loading and unloading cost of the field bridge. Then, according to the characteristics of the model, a genetic algorithm combined with Tabu search is designed to optimize the solution. The memory function of Tabu search is introduced into mutation operation to enhance the climbing ability of genetic algorithm. Finally, the effectiveness of the integrated optimization model and the proposed algorithm is verified based on an example. The research results of this paper are helpful to improve the operation level of container terminal yard, especially to provide decision support for static yard bridge scheduling in the mixed pile box area. At the same time, it can be used for reference in theory and method for the scheduling optimization of large equipment in other logistics fields. The optimization method developed for mixed stack container terminal yard and bridge scheduling has reference significance for solving the optimization problems of similar complex systems. The purpose of this study is to solve the complex and real-time problems of container terminals, which is of great significance to the actual production of container terminals in China.
【学位授予单位】：大连海事大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U691.3

【参考文献】