移动电子商务环境下物流快递人员服务路线动态优化方法研究

发布时间：2018-08-14 17:40

【摘要】：移动电子商务的快速发展给物流快递行业带来了新的机遇和挑战。在移动电子商务环境下,结合现有的全球定位系统和全球移动通讯系统等技术的发展,物流快递企业能够实时获取顾客、取货车辆和道路交通等信息。在移动电子商务环境下,物流快递企业能够对在线顾客的快递服务请求做出快速响应并有效满足顾客需求,从而提高物流快递运作效率和服务质量,这也将会吸引更多的顾客使用移动终端发送快递服务请求,同时促进物流快递行业和移动电子商务的协调发展;能够合理利用物流快递企业的资源,有效满足顾客需求。本文结合移动电子商务的特点,分析其对物流快递取货过程带来的影响,即在执行取货任务的过程中,随时有动态信息的产生,当有动态信息发生时,原优化的取货服务路线就会变得次优或者不可行,因此需要利用一种算法能够快速的合并动态信息,对服务路线进行动态优化。本文通过变时长的滚动时域设置和引入虚拟顾客的方式,将服务路线动态优化过程转化为相应时间点的静态车辆路径问题。将整个取货过程分为两个阶段:初始静态阶段和动态阶段,并根据两个阶段的特点建立了相应的数学规划模型。对于建立的数学规划模型,本文采用两阶段算法求解。第一阶段利用改进贪婪算法快速生成模型的初始解,第二阶段通过改进模拟退火算法对生成的初始解进行优化,得到系统最优解。利用的改进贪婪算法属于构建型算法,基于传统贪婪算法的思想,分别在求解速度和求解质量两个方面做了改进。该改进后的算法求解速度快,能够在动态信息发生后将其与尚未被服务的顾客信息结合,优化得到较满意的取货路线方案。改进模拟退火算法是在传统模拟退火算法的基础上,在邻域操作方法、加入记忆装置和设置终止准则三个方面进行了改进。将设计的改进模拟退火算法通过求解相同的算例得到的最优解与禁忌搜索算法和改进后的启发式算法相比,求解质量得到提高。通过两种算法实现对于移动电子商务环境下物流快递人员服务路线的动态优化。
[Abstract]:The rapid development of mobile e-commerce brings new opportunities and challenges to the logistics express industry. In the environment of mobile electronic commerce, with the development of global positioning system (GPS) and global mobile communication system (GMS), logistics express enterprises can obtain information such as customers, pick-up vehicles and road traffic in real time. In the environment of mobile electronic commerce, logistics express enterprises can respond to the online customers' express service request quickly and meet the customer's demand effectively, so as to improve the efficiency and service quality of logistics express service. This will also attract more customers to use mobile terminals to send express service requests, and promote the coordinated development of logistics express industry and mobile electronic commerce, which can make rational use of the resources of logistics express enterprises, and effectively meet the needs of customers. Based on the characteristics of mobile electronic commerce, this paper analyzes the influence of mobile electronic commerce on the process of receiving goods by express delivery, that is, in the process of carrying out the task of picking up goods, dynamic information is generated at any time, and when there is dynamic information, The original optimized delivery service route will become suboptimal or unfeasible, so it is necessary to use an algorithm to quickly merge dynamic information and optimize the service route dynamically. In this paper, the dynamic optimization process of service route is transformed into the static vehicle routing problem at the corresponding time point by setting the rolling time domain with variable time and introducing the virtual customer. The whole process is divided into two stages: initial static stage and dynamic stage, and the corresponding mathematical programming model is established according to the characteristics of the two stages. For the established mathematical programming model, this paper uses two-stage algorithm to solve the problem. In the first stage, an improved greedy algorithm is used to quickly generate the initial solution of the model. In the second stage, the generated initial solution is optimized by an improved simulated annealing algorithm, and the optimal solution of the system is obtained. The improved greedy algorithm is a constructive algorithm. Based on the idea of the traditional greedy algorithm, this paper improves the speed and quality of the solution respectively. The improved algorithm can solve the problem quickly and can combine the dynamic information with the customer information which has not been served. The improved simulated annealing algorithm is based on the traditional simulated annealing algorithm. It is improved in three aspects: neighborhood operation method, adding memory device and setting termination criteria. Compared with the Tabu search algorithm and the improved heuristic algorithm, the quality of the improved simulated annealing algorithm is improved compared with the Tabu search algorithm and the improved heuristic algorithm. Two algorithms are used to realize the dynamic optimization of the service route of logistics couriers under the environment of mobile electronic commerce.
【学位授予单位】：山东科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F252;TP18

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