基于改进遗传算法的物流配载系统的设计与实现

发布时间：2018-06-12 16:50

本文选题：物联网 + RFID　；参考：《哈尔滨工业大学》2015年硕士论文

【摘要】：随着经济的快速发展,对物流企业的配送效率和成本控制都提出了越来越高的要求,传统的物流管理模式已经无法适应日益激烈的市场竞争环境。配载问题作为物流过程中的一个最具代表性的难题,由于现实约束条件较多,货物规模巨大,很难得到一个最优的方案,通常解决这类问题的方法是利用启发式算法得到一个优化解,但是优化解的质量和求解效率因模型和算法不同差异较大。本文首先对大宗商品物流的实际需求进行了详细的描述和分析,根据需求分析结果对基于多现实的约束条件下的货物配装问题和路径规划问题进行了深入的研究,并在货物配装问题和路径规划问题模型的基础上进行了归一量化处理,建立了配载问题的组合优化数学模型;然后通过采用可行解变换策略和动态自适应交叉、变异策略对遗传算法进行改进,提升了算法搜索效率和优化解的质量,运用改进后的遗传算法对配载问题进行优化求解,并通过实验对算法进行了测试,证明了算法的有效性;最后设计并实现了一套具有配载功能的综合物流管理系统,该系统采用配载模型和物联网相关技术对物流企业的三大要素“人、车、物”进行综合管理,实现了物流企业信息化、自动化、正规化的工作流程。通过对系统功能的实现,不仅能够改变企业传统的手工模式,实现了灵活的、自动的运行模式,提高物流管理的整体性能,而且还能够利用货物和车辆的信息数据来优化配载问题,从提高车辆装载效率和缩短车辆行驶里程两方面进行优化,为企业车辆调度提供决策支持,有效提高企业生产效率、控制成本支出。
[Abstract]:With the rapid development of economy, the distribution efficiency and cost control of logistics enterprises are required more and more high. The traditional logistics management mode has been unable to adapt to the increasingly fierce market competition environment. As one of the most representative problems in the process of logistics, the stowage problem is difficult to get an optimal solution because of the large scale of goods and many practical constraints. A heuristic algorithm is usually used to obtain an optimal solution, but the quality and efficiency of the optimal solution vary greatly with different models and algorithms. In this paper, the actual demand of commodity logistics is described and analyzed in detail. According to the results of demand analysis, the cargo loading problem and route planning problem based on multi-reality constraints are deeply studied. Based on the model of cargo loading problem and path planning problem, the combinatorial optimization mathematical model of loading problem is established, and then the feasible solution transformation strategy and dynamic adaptive crossover are adopted. The mutation strategy improves the search efficiency and the quality of the optimal solution. The improved genetic algorithm is used to solve the stowage problem. The algorithm is tested by experiments and the validity of the algorithm is proved. Finally, a set of integrated logistics management system with stowage function is designed and implemented. The system uses stowage model and Internet of things technology to manage the three main factors of logistics enterprise: "person, car, object". Logistics enterprises to achieve information, automation, formalization of the workflow. Through the realization of the system function, not only can the traditional manual mode of enterprise be changed, but also the flexible and automatic operation mode can be realized, and the overall performance of logistics management can be improved. And it can optimize the stowage problem by using the information data of goods and vehicles, which can improve the efficiency of vehicle loading and shorten the mileage of vehicles, which can provide decision support for vehicle scheduling, and effectively improve the efficiency of enterprise production. Control cost and expenditure.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TP311.52;TP18

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