基于改进萤火虫算法的集装箱堆场出口箱箱位分配问题研究

发布时间：2018-03-29 15:26

本文选题：集装箱码头　切入点：堆场　出处：《大连海事大学》2017年硕士论文

【摘要】：随着全球经济的快速发展,国际和区域间的货运贸易越来越频繁,集装箱吞吐量需求日益增加,从而导致码头堆场的空间资源与集装箱吞吐量的矛盾也不断加剧。由于拓展港口码头的空间资源耗时耗力并且需要花费大量资金,所以提高堆场现有空间资源利用率已成为解决该矛盾的一种经济而有效的手段。出口箱堆存箱位的分配直接影响着船舶停港时间、装卸船效率乃至整个港口生产效率的高低。故而在有限的空间资源下,研究出口箱箱位分配问题已经成为港航运输和自动化集装箱码头等相关领域的研究热点问题之一。本文通过优化出口箱在堆场中的堆存箱位,达到充分利用堆场空间资源的目的。根据堆场出口箱箱位分配的基本原则,在不同目的港和重量等级混合堆存模式下,考虑总翻箱量,集装箱均衡分配和运输距离等问题,以及其他相关约束条件,建立了堆场出口箱箱位优化分配问题的数学模型。因该问题是复杂离散组合优化问题,具有NP难度,很难用传统方法进行求解。本文采用较为新颖的萤火虫算法进行求解,为了避免算法过早陷入局部最优,同时为了增加种群的多样性、加快收敛速度,提出一种并行自适应萤火虫算法(PAFA)。其主要思想是基于离散问题的实质和萤火虫算法的基本原理,引入遗传算法的交叉、变异算子,先将标准萤火虫算法进行离散化处理,对个体间的距离等进行重新定义,使其适用于离散问题的求解;进而基于自适应的思想,将位置更新改造为自适应的位置更新方式;同时采用并行策略,将种群分成两个子群体,一个子群体侧重向最优个体的学习以加快收敛,另一个子群体在算法不同时期兼顾搜索和开发,两者定期进行信息交流,以提高算法的整体性能。文中通过标准TSPLIB测试库中两个旅行商问题对所提算法进行了测试与验证,结果表明了其解决离散组合优化问题的可行性和有效性。进一步,以大连大窑湾集装箱港区相关航线的堆场出口箱箱位分配问题为工程背景,将提出算法应用到前述的数学模型之中,对两种简化工况下的箱位分配问题进行了仿真与测试。结果表明,本文所提算法对求解该问题有效,给出了较好的箱位分配方案,能够提高堆场空间资源利用率,且降低了作业和运输成本。本文的研究工作为后续深入研究箱位分配问题,乃至所提算法的工程实用化提供了启发和借鉴,具有一定的理论意义和应用价值。
[Abstract]:With the rapid development of the global economy, international and interregional freight trade is becoming more and more frequent, and the demand for container throughput is increasing day by day. As a result, the contradiction between the space resources of the terminal yard and the throughput of the container is becoming more and more serious, because the expansion of the space resources of the port terminal is time-consuming and time-consuming and requires a lot of money. Therefore, increasing the utilization rate of existing space resources in the yard has become an economic and effective means to solve this contradiction. The efficiency of loading and unloading ships and even the production efficiency of the whole port. Therefore, in the limited space resources, The research on the allocation of export container space has become one of the hot issues in the related fields, such as port and shipping transportation and automatic container terminal, etc. In this paper, by optimizing the storage space of export container in the yard, In order to make full use of the space resources of the yard, according to the basic principle of the allocation of the container space at the outlet of the yard, under the mixed storage mode of different destination ports and weight classes, the problems of the total turnover volume, the balanced distribution of the containers and the transportation distance are considered. The mathematical model of the optimal allocation of the box space at the exit of the yard is established, which is a complex discrete combinatorial optimization problem with NP difficulty. In this paper, a novel firefly algorithm is used to solve the problem, in order to avoid prematurely falling into local optimum, to increase population diversity and to speed up convergence. A parallel adaptive firefly algorithm (PAFAA) is proposed, which is based on the essence of the discrete problem and the basic principle of the firefly algorithm. The crossover and mutation operators of genetic algorithm are introduced to discretize the standard firefly algorithm. The distance between individuals is redefined to make it suitable for solving discrete problems. Then, based on the adaptive idea, the position update is transformed into an adaptive position updating method. At the same time, the parallel strategy is adopted. The population is divided into two subpopulations, one focusing on learning from the optimal individual to accelerate convergence, the other taking into account search and development at different stages of the algorithm, where information is exchanged on a regular basis. In order to improve the overall performance of the algorithm, the proposed algorithm is tested and verified by two traveling salesman problems in the standard TSPLIB test library. The results show that the proposed algorithm is feasible and effective in solving discrete combinatorial optimization problems. Based on the problem of allocation of export container space in Dalian Dayaowan container port area, the proposed algorithm is applied to the above mathematical model. The simulation and test of the box allocation problem under two simplified working conditions are carried out. The results show that the algorithm proposed in this paper is effective in solving the problem, and a better box allocation scheme is given, which can improve the utilization ratio of space resources in the storage yard. The research work in this paper provides inspiration and reference for the further study of box allocation and even the practical application of the proposed algorithm, which has a certain theoretical significance and application value.
【学位授予单位】：大连海事大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U691.3;TP18

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