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论文编号：	15945
作者编号：	2320223893
上传时间：	2025/12/22 13:09:00
中文题目：	A公司生鲜供应链物流模式优化研究
英文题目：	Optimization of the Fresh Food Supply Chain Logistics Model in Company A
指导老师：	李凯
中文关键字：	关键词：生鲜；物流模式；评价优化；
英文关键字：	Key Words: Fresh Food; Logistics Model; Evaluation and Optimization
中文摘要：	近年我国生鲜电商发展迅速，到2025年，交易规模或突破1.3万亿元，年均复合增长率一直维持在28%以上；随着消费升级的到来，用户对于生鲜的需求不再停留在能充饥的地步，而更多是满足于追求更高质量、更高品类以及更加便利的消费体验，也必然会倒逼着生鲜物流在时效、质量以及稳定性等方面有更高的要求。但目前，生鲜物流依旧存在配送延误、温控失效、服务水平参差不齐、季节性运力不足等问题，制约着生鲜物流行业的发展。 本研究以A公司为例，对A公司的生鲜供应链物流模式的优化方向进行了系统性的探讨，在总结相关文献的基础上并结合了实地调研的数据结果可知A公司在物流运作过程中出现的一些比较明显的问题主要有：跨区配送时效不稳定、县域网络覆盖不健全和冷链资源应对需求波动时柔性不够等问题。通过对A公司生鲜供应链物流模式存在问题的研究，通过建立一个完整的指标评价体系来进行具体问题诊断。将综合评价指标体系归纳成6个维度，分别为时效性、成本控制、服务品质、网络覆盖、技术应用和绿色可持续，运用AHP（Analytic Hierarchy Process）层次分析法对各个评价指标的权重值进行了研究分析。“跨省运输时效”和“温控达标率”的权重值最高，达到了0.181和0.275,说明了在生鲜物流系统里面，对时效精准度和品质稳定性的要求较高。 运用TOPSIS法分析得出A公司现有实施的产地直发、区域分仓、前置仓这3种模式综合贴近度分别是：前置仓模式为0.677,区域分仓为0.549,产地直发为0.380。由上可见，前置仓模式综合得分最高，其在最后端配送时效性、温控一致性和客户体验方面均优于区域分仓和产地直发模式。基于评价结果，本文构建了“运输距离—商品品类—时效要求—成本结构”为要素的多维决策模型，明确了不同模式适用场景以及优化路径，从网络布局、技术赋能、包装循环、调度优化等维度提出整套策略体系。 该研究结果对A公司生鲜物流模式科学选用和运营优化提升起到指导作用，并能够为同行业的其他物流企业的运营体系完善、降低成本、提高效益以及升级服务等提供借鉴。
英文摘要：	In recent years, China's fresh produce e-commerce market has witnessed explosive growth. It is expected that the transaction scale of this sector will rise to 1.3 trillion yuan by 2025, with an annual compound growth rate (CAGR) remaining steadily above 28%. Driven by the wave of consumption upgrading, consumers' demand for fresh produce is no longer limited to basic supply guarantee, but is shifting toward higher quality, greater product variety, and more convenient consumption. This undoubtedly places more stringent requirements on the timeliness, quality, and stability of fresh produce logistics. However, at present, fresh produce logistics still generally faces prominent issues such as delivery delays, temperature control failures, uneven service quality, and seasonal capacity shortages, which severely restrict the healthy development of the industry. The thesis uses the fresh food supply chain logistics model optimization of Company A as an example to carry out a systematic study, and based on the literature review and field investigation, Company A’s existing logistics problems were analyzed, including unstable cross-regional delivery time; shortcoming of county-level coverage; lack of flexibility of cold chain resource equipment. Then, according to the actual situation of logistics company, an assessment index system was established which included the six aspects of timeliness, cost control, service quality, network coverage, technology application, green sustainable development. Then, AHP (Analytic Hierarchy Process) method is used to quantify every single element according to their weighting. On the one hand, the model indicates that the weight values“cross-province transportation timeliness”(0.181) and“temperature control compliance rate”(0.275) are the highest, with important implications in timely and reliable ordering and product supply. With respect to the logistics models commonly used by Company A, the TOPSIS approach was used to evaluate the direct shipment from production area, regional warehouse and forward warehouse in turn, the forward warehouse model obtained a comprehensive closeness grade of 0.677, which is much higher than the regional warehouse model(0.549) and the direct shipment model(0.380), this forward warehouse model is obviously superior to the other two modes in terms of speed of last mile, temperature control uniformity and overall experience of customers. On these grounds, we further improved the model through a comprehensive decision-making framework based on "transportation distance-product categories-timeliness requirements-cost structure", outlined the specific business application scope and optimization directions corresponding to different types of models, pointed out the relevant logistics strategy paths such as the arrangement of the business flow network, the incorporation of technology, the reuse of packaging, and the dispatch strategy. The findings of this study provide guidance for the scientific selection and operational optimization of A Company's fresh produce logistics model, and can serve as a reference for other logistics enterprises in the same industry to improve their operational systems, reduce costs, enhance efficiency, and upgrade services.
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