基于改进最大覆盖模型在生鲜电商O2O社区店选址应用研究

发布时间：2019-06-07 19:51

【摘要】：生鲜电商发展越来越成熟,生鲜冷链配送市场也随之兴起,引领物流产业,在众多生鲜电商的发展中,运输配送环节备受关注,不仅关乎配送成本,也影响到末端消费者的时间满意度。所以线下社区店布局,利用O2O的优势来发展维护现有消费客户,提升用户体验的做法被越来越多的专家和企业所认同,甚至已经开始了市场探索和尝试。而在生鲜电商O2O模式的探索过程中,线下社区店的布局选址则变成了最重要的问题。本文研究生鲜电商社区店的布局选址问题,针对传统商业设施选址问题研究成果在需求覆盖程度和服务时间体现的不足,文章利用最大覆盖选址模型和服务覆盖路径概念解决需求覆盖和服务时间的问题。生鲜电商社区店的选址问题和传统商业设施选址及公共服务设施选址存在差异,通过对比传统选址方法中各类影响因素分析,部分影响因素存在关联性,总结出本文社区店选址内外部影响因素,主要考虑影响因素为人口规模、人口结构、收入水平,通过具体数据分析得到对应影响系数α、β、m,每个影响因素在计算各社区电商需求量时起决定作用,根据影响系数计算出每个需求点的需求量。需求量是最终的目标最优决策依据,同时社区店选址考虑到建设成本和建设数量等约束条件,使用最大覆盖模型满足所有需求点被社区店覆盖,同时满足覆盖的需求量最大。本文在建模的过程中考虑到生鲜电商的特性和消费者需求,融入了消费者的时间满意度,在判断社区覆盖与否时提出覆盖路径概念。由于提供配送服务速度和距离已知,根据配送速度和配送距离来确定每个点之间的配送时间,以时间为消费者服务满意的判断标准,时间越短满意度越高,当时间超出预定的范围,判定该区域不在覆盖范围内。本文通过定性分析和定量分析相结合,给出了适用该领域的最大覆盖选址模型,从时间和覆盖路径角度重新定义了该模型,并通过具体案例求解,给出最优方案。
[Abstract]:The development of fresh e-commerce is becoming more and more mature, and the fresh cold chain distribution market is also rising, leading the logistics industry. in the development of many fresh e-commerce, transportation and distribution links have attracted much attention, which is not only related to the cost of distribution. It also affects the time satisfaction of end consumers. Therefore, the offline community store layout, using the advantages of O2O to develop and maintain existing consumer customers, improve the user experience has been recognized by more and more experts and enterprises, and has even begun to explore and try the market. In the process of exploring the O2O model of fresh e-commerce, the layout and location of offline community stores has become the most important problem. In this paper, the layout and location of fresh ecommerce community stores is studied, and the research results on the location of traditional commercial facilities are insufficient in the degree of demand coverage and service time. In this paper, the maximum coverage location model and the concept of service coverage path are used to solve the problem of demand coverage and service time. There are differences between the location problem of fresh e-commerce community store and the location of traditional commercial facilities and public service facilities. By comparing all kinds of influencing factors in the traditional location method, some of the influencing factors are related. This paper summarizes the internal and external factors of community store location, mainly considering the population size, population structure, income level, through the specific data analysis to obtain the corresponding influence coefficients 伪, 尾, m, Each influencing factor plays a decisive role in calculating the demand of e-commerce in each community, and the demand of each demand point is calculated according to the influence coefficient. Demand is the final goal of the optimal decision-making basis, at the same time, considering the construction cost and construction quantity and other constraints, the maximum coverage model is used to meet all the demand points covered by the community store, and the demand to meet the coverage is the largest. In the process of modeling, considering the characteristics of fresh e-commerce and consumer demand, the time satisfaction of consumers is integrated, and the concept of coverage path is put forward when judging whether the community is covered or not. Since the speed and distance of providing distribution service are known, the distribution time between each point is determined according to the distribution speed and distribution distance, and the shorter the time is, the higher the satisfaction is. When the time exceeds the predetermined range, it is determined that the area is not covered. In this paper, through the combination of qualitative analysis and quantitative analysis, the maximum coverage location model suitable for this field is given, the model is redefined from the point of view of time and coverage path, and the optimal scheme is given by solving a concrete case.
【学位授予单位】：浙江工商大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F326.6

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