大型船舶物资补给理论搬运时间优化问题研究

发布时间：2019-06-03 20:39

【摘要】：随着军事格局的日益变化,建造可以长时间在海上航行的大型船舶的需求愈来愈多。物资补给是影响此类船舶续航能力和机动性的重要因素,在较短的时间完成物资补给对于海上航行的大型船舶而言显得尤为重要,研究物资补给理论搬运时间优化问题、探讨优化模型和计算方法,具有重要的理论和现实意义。本文以某大型船舶物资补给为背景,建立理论搬运时间优化模型,主要从转运环节物流量控制和转运策略选择两个方面对物资补给过程进行优化,其决策目标是使搬运时间最短。从物资种类和补给口数量两个因素来抽象物资补给过程,将优化问题分为单物资单补给口、单物资双补给口、多物资单补给口、多物资双补给口四种情形。对于单物资补给情形,归结为网络最大流问题,采用Ford-Fulkerson算法进行计算优化,最大化系统流量,意即搬运时间最短。对于多物资补给情形,优化内容为码头至船舶混合发货的组合方案,即转运策略,此种情形属于NP-hard问题,与车间调度问题类似,基于事件驱动思想,建立了优化模型,以码头到船舶的混合发货方案为变量,以搬运时间最小为目标函数;采用遗传算法进行求解,对变量进行矩阵编码,并提出矩阵转换方式使交叉之后产生的非法染色体合法化。由于标准遗传算法容易陷入局部最优且收敛较慢,本文在标准遗传算法的基础上进行改进。最后以某一具体实例为背景,验证了本文模型和算法的有效性,也证明了改进遗传算法较标准遗传算法能得到更好的解并加快收敛速度。
[Abstract]:With the increasing change of military pattern, there is more and more demand for the construction of large ships that can sail at sea for a long time. Material supply is an important factor affecting the endurance and maneuverability of this kind of ship. It is particularly important for large ships sailing at sea to complete the material supply in a relatively short time. The optimization of material supply theory handling time is studied. It is of great theoretical and practical significance to discuss the optimization model and calculation method. Based on the material supply of a large ship, this paper establishes a theoretical transportation time optimization model, which mainly optimizes the material supply process from two aspects: the flow control of the transfer link and the selection of the transportation strategy. Its decision-making goal is to minimize the handling time. The process of material supply is abstracted from the two factors of material type and supply port quantity. The optimization problem is divided into four cases: single material single supply port, single material double supply port, multi-material single supply port and multi-material double supply port. For the case of single material supply, the problem of network maximum flow is reduced to the problem of network maximum flow. Ford-Fulkerson algorithm is used to optimize the calculation and maximize the system traffic, that is to say, the handling time is the shortest. For the case of multi-material supply, the optimization content is the combination scheme of mixed shipment from wharf to ship, that is, the transportation strategy, which belongs to the NP-hard problem, which is similar to the job shop scheduling problem. Based on the event-driven idea, the optimization model is established. The mixed shipping scheme from wharf to ship is taken as the variable, and the minimum handling time is taken as the objective function. Genetic algorithm is used to solve the problem, the variables are encoded by matrix, and the matrix transformation method is proposed to legitimize the illegal chromosomes after crossing. Because the standard genetic algorithm is easy to fall into local optimization and the convergence is slow, this paper improves on the basis of the standard genetic algorithm. Finally, based on a specific example, the effectiveness of the model and algorithm is verified, and it is proved that the improved genetic algorithm can get better solution and accelerate the convergence speed than the standard genetic algorithm.
【学位授予单位】：华中科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U693

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