输出型煤炭码头卸车生产调度优化模型和方法研究

发布时间：2018-01-15 02:07

本文关键词：输出型煤炭码头卸车生产调度优化模型和方法研究　出处：《武汉理工大学》2014年硕士论文　论文类型：学位论文

【摘要】：港口企业的装卸生产调度既是工程技术难题，，也是一些复杂的学术问题。为了提高港口生产效率，国内外许多学者一直在探索解决此类问题的方法。基于输出型煤炭码头的装卸生产过程，以卸车优化调度问题为研究对象，本文建立了以火车在港时间最少为目标的数学模型，研究了优化算法，实现了调度问题的求解。主要研究成果如下：本文首先分析了输出型煤炭码头卸车作业调度的各种关联因素，发现了卸车调度具有研究对象信息繁杂、调度系统可变、可选作业流程多样、解信息量大等特性，进一步研究了卸车作业调度的约束关系，并建立现实作业中的唯一性、作业性质、堆场以及卸车工艺等四个约束关系的数学方程，以火车在港时间最短为优化目标建立了卸车作业调度的混合整数规划数学模型，通过实际案例应用验证了模型的准确性和工程适用性。鉴于卸车作业调度的数学模型的求解是一个NP-Hard问题，本文进一步研究了港口生产调度过程，提出了一个递阶主副型复合算法：面向火车到达事件的启发式搜索算法和面向翻车机空闲事件的启发式搜索算法。基于未来一段时间内火车达到计划，该算法首先运用面向火车到达事件的启发式搜索算法求解火车作业计划，然后运用面向翻车机空闲事件的启发式搜索算法修正优化火车计划，最终得到更优的火车作业计划。该算法以国内某煤炭码头为对象，进行了实际应用，取得了较好的效果。为寻求更优的求解算法，本文对调度模型进行了更深入的研究，设计了基于类编码的遗传算法，针对卸车调度的独特性，提出了新的个体编码解码方法，构造了更加适用于实际卸车调度作业的适应度函数，通过实验得到了更加实用可靠的两种终止规则相结合的混合终止条件。遗传算法以同一个煤炭码头为对象，进行实际应用，取得了更好的效果。通过具体案例与大量算例实验对两种算法对比分析，遗传算法解的质量更优，灵活性更高，虽然其计算耗时较长，但可以采取有效措施弥补。因此，遗传算法相比于启发算法更适用于煤炭码头的实际生产。
[Abstract]:The scheduling of loading and unloading production in port enterprises is not only a difficult problem of engineering and technology, but also a complex academic problem in order to improve the efficiency of port production. Many scholars at home and abroad have been exploring ways to solve this problem. Based on the output coal wharf loading and unloading production process, the optimal scheduling of unloading is the research object. In this paper, a mathematical model aiming at the least time of the train in port is established, and the optimization algorithm is studied, and the solution of the scheduling problem is realized. The main research results are as follows: This paper first analyzes the output coal wharf unloading operation scheduling of various related factors, found that unloading scheduling has complex research object information, scheduling system variable, optional operation process is diverse. In order to solve the characteristics of large amount of information, the constraint relation of unloading operation scheduling is further studied, and the mathematical equations of the four constraints in practical operation, such as uniqueness, nature of operation, yard and unloading process, are established. The mixed integer programming mathematical model of unloading operation scheduling is established with the shortest train time in port as the optimization objective. The veracity and engineering applicability of the model are verified by practical cases. In view of the fact that the solution of the mathematical model of unloading operation is a NP-Hard problem, this paper further studies the process of port production scheduling. This paper presents a hierarchical master-pair composite algorithm: a heuristic search algorithm for train arrival events and a heuristic search algorithm for idle events in rollers, based on the plan of train arrival in a certain period of time in the future. The algorithm first uses the heuristic search algorithm for train arrival event to solve the train operation plan, and then uses the heuristic search algorithm for the idle event of the dumper to modify and optimize the train plan. Finally, a better train operation plan is obtained. The algorithm is applied to a coal wharf in China, and good results are obtained. In order to find a better algorithm, this paper studies the scheduling model more deeply, designs a genetic algorithm based on class coding, and proposes a new individual coding decoding method in view of the uniqueness of unloading scheduling. The fitness function, which is more suitable for the actual unloading dispatching, is constructed, and a more practical and reliable hybrid termination condition is obtained by experiments. The genetic algorithm takes the same coal wharf as the object. The practical application has achieved better results. Through the comparison and analysis of the two algorithms through specific cases and a large number of numerical examples, the results show that the solution of genetic algorithm is of better quality and higher flexibility, although it takes a long time to calculate, it can take effective measures to make up for it. Genetic algorithm is more suitable for coal wharf than heuristic algorithm.
【学位授予单位】：武汉理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U691.3

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