O2O模式下连锁零售网点需求预测及资源调度研究

发布时间：2018-01-13 02:24

本文关键词：O2O模式下连锁零售网点需求预测及资源调度研究　出处：《南京邮电大学》2016年硕士论文　论文类型：学位论文

【摘要】：近年来,在电子商务快速发展的冲击下,传统消费市场整体表现疲软,传统零售企业纷纷试水O2O模式转型升级。O2O的核心是线上线下互动融合,十分注重用户体验,缺失线下体验的O2O是不完整的,甚至导致整个模式失效。而保证产品的可获性作为线下体验的第一步,变得尤为重要。保证产品的可获性无非就是需求和供应两方面的内容:需求方面而言,为了提前掌握各网点的需求情况,需要对各网点的需求进行预测。O2O模式下环境复杂,各网点的需求受到线上线下很多不确定性随机因素的影响,而且,各零售网点的覆盖范围有限,随机因素产生的影响较大,传统的预测方法无法将随机因素的影响考虑进来,本文拟用概率排序模型进行需求预测;供应方面而言,为了既保证满足需求,又节省调度成本,需要在需求预测的基础上合理进行资源调度,寻找最优调度方案。由于概率排序型预测仅仅知道各自然状态出现概率的大小顺序而不知道其具体数因而无法准确地计算期望值,只能求出期望值的最大值和最小值。也就是说,需求预测结果为区间概念,在此基础上进行资源调度考虑用区间规划模型。基于此,本文主要研究工作如下:(1)对O2O模式下连锁零售企业的运营过程进行深入分析,探讨O2O模式下连锁零售企业资源调度过程和影响零售网点需求量的因素;(2)充分考虑未来可能的随机因素对各零售网点需求预测的影响,建立基于概率排序的需求预测模型;(3)以需求预测结果为基础展开资源调度研究,建立区间规划模型,并将其转化为确定性规划问题进行求解;(4)最后给出一个案例演示需求预测与资源调度的计算过程。本文以连锁零售企业各网点为研究对象,从供需两方面的视角切入,建立了基于概率排序的需求预测模型和资源调度区间规划模型,给出了O2O模式下有效保证产品可获性从而提升客户体验的方案。研究贴合O2O实践中的具体问题,具备很强的现实参考意义。
[Abstract]:In recent years, under the impact of the rapid development of e-commerce, the overall performance of the traditional consumer market is weak. The core of the transformation and upgrading of the traditional retail enterprises is online and offline interaction. Very attention to user experience, lack of offline experience of O2O is incomplete, or even lead to the failure of the entire mode. And ensure the product availability as the first step of offline experience. It is particularly important to ensure that the availability of products is nothing more than demand and supply content: the demand side, in order to grasp the demand situation in advance of each network. It is necessary to predict the demand of each network under the complex environment under the mode of .O2O. The demand of each network is affected by a lot of uncertain random factors on line and under line, and the coverage of each retail network is limited. The influence of random factors is great, the traditional forecasting method can not take the influence of random factors into account, this paper intends to use the probability ranking model to forecast demand; On the supply side, in order to meet the demand and save the scheduling cost, it is necessary to reasonably schedule resources on the basis of demand forecasting. Search for the optimal scheduling scheme. Because the probabilistic ranking prediction only knows the order of occurrence probability of each natural state, and does not know its specific number, it can not accurately calculate the expected value. Only the maximum and minimum expected values can be obtained. That is to say, the demand forecast results are interval concept, and on this basis, the resource scheduling is considered by interval programming model. The main research work of this paper is as follows: (1) deeply analyzing the operation process of chain retail enterprises under O _ 2O mode. This paper discusses the resource scheduling process of chain retail enterprises under O _ 2O mode and the factors influencing the demand of retail outlets. 2) considering the influence of possible random factors on the demand forecast of retail outlets in the future, a demand forecasting model based on probability ranking is established. 3) based on the demand forecast results, the research on resource scheduling is carried out, and the interval programming model is established, which is transformed into a deterministic programming problem to solve the problem. Finally, a case is given to demonstrate the calculation process of demand forecasting and resource scheduling. In this paper, the retail chain outlets as the research object, from the point of view of supply and demand. The demand forecasting model and resource scheduling interval programming model based on probability ordering are established. In this paper, a scheme to effectively guarantee the product availability and improve customer experience under the O _ 2O mode is presented. It is of great practical significance to study the specific problems in the practice of O _ 2O.
【学位授予单位】：南京邮电大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：F724.6;F721.7

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