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论文编号：	15715
作者编号：	2320233832
上传时间：	2025/12/9 15:26:42
中文题目：	K公司供应链配送网络优化策略研究
英文题目：	The Research on Optimization Strategy of K Company''s Supply Chain Distribution Network
指导老师：	梁峰
中文关键字：	耐火材料企业；供应链配送网络；网络优化；降本增效；安全库存
英文关键字：	Refractory Materials Enterprise；Supply Chain Distribution Network；Network Optimization；Cost Reduction and Efficiency Improvement；Safety Stock
中文摘要：	在制造业竞争日趋激烈和国家“双碳”政策不断推进的背景下，企业如何通过供应链优化实现降本增效与绿色发展，已成为管理者必须面对的核心问题。配送网络作为供应链的重要环节，直接决定了企业的运营成本、服务水平和市场响应速度。K公司在天津滨海新区设有唯一生产工厂，并依托大连、太原、巩义、新密、武汉、上海、成都、广州、唐山等9个第三方仓库及工厂自有仓库构建了覆盖全国的配送体系。然而，该网络在实际运行过程中暴露出明显问题：部分仓库利用率偏低，长期承担高额的固定费用；运输结构过度依赖公路直发，导致运输费用持续上升；水运等低碳运输方式应用不足，使碳排放压力不断加大；同时在部分区域配送环节中存在路径冗余，资源配置效率不高。 针对这些问题，本文对K公司近几年的订单需求分布、仓库运营状况和运输方式选择进行了系统分析，明确了当前网络的主要瓶颈。在此基础上，结合企业的运营目标和政策要求，构建了以“总成本最小化、服务水平保障和碳排放控制”为核心的优化模型。模型设计以实际业务为导向，重点考虑三个方面：一是仓库布局的调整与取舍，避免因冗余仓库导致的费用浪费；二是运输方式的结构优化，在保障时效的前提下提高水运比例，以实现成本下降和碳排放减少；三是补货与配送节奏的合理规划，使工厂与各仓库之间、仓库与客户之间的物流衔接更加顺畅。 在模型求解过程中，采用遗传算法对仓库配置、运输路径和补货策略进行优化搜索。该方法能够在复杂的组合问题中快速收敛，获得符合企业运营要求的可行方案。通过对不同情境下的方案进行对比与评估，可以清晰展现仓储网络调整与运输模式优化对成本控制与绿色发展的实际作用。 本研究立足于企业实际问题，采用定量分析与优化方法，为K公司提供了具有可操作性的改进方案。研究结论表明，配送网络优化不仅是企业降低成本的关键途径，也是实现绿色发展和增强市场竞争力的重要手段，对K公司未来的运营实践具有直接指导意义。
英文摘要：	In the context of increasingly fierce competition in the manufacturing industry and the continuous advancement of China’s “dual carbon” policy, how enterprises can achieve cost reduction, efficiency improvement, and green development through supply chain optimization has become a core issue for managers. As a crucial link in the supply chain, the distribution network directly determines a company’s operating costs, service level, and market responsiveness. K Company has a single production plant located in Tianjin Binhai New Area and relies on nine third-party warehouses in Dalian, Taiyuan, Gongyi, Xinmi, Wuhan, Shanghai, Chengdu, Guangzhou, and Tangshan, together with its factory warehouse, to establish a nationwide distribution system. However, in practice, this network reveals several issues: some warehouses suffer from low utilization yet bear high fixed costs; the transportation structure relies excessively on direct road delivery, causing transportation expenses to keep rising; the application of low-carbon modes such as waterway transport remains insufficient, thereby intensifying carbon emission pressures; and in certain regions, distribution paths are redundant, leading to inefficiency in resource allocation. To address these problems, this study systematically analyzes K Company’s order demand distribution, warehouse operations, and transportation mode choices in recent years, identifying the main bottlenecks of the current network. On this basis, and in line with corporate operational objectives and policy requirements, a multi-objective optimization model is developed with a focus on minimizing total costs, ensuring service level, and controlling carbon emissions. The model is business-oriented and emphasizes three key aspects: first, warehouse layout adjustment and elimination to avoid cost waste caused by redundant facilities; second, optimization of the transportation structure by increasing the share of waterway transport while ensuring service timeliness, thereby achieving lower costs and reduced emissions; third, rational planning of replenishment and distribution rhythms to enhance the coordination between the factory and warehouses, as well as between warehouses and customers. In solving the model, a genetic algorithm is applied to optimize warehouse configuration, transportation routes, and replenishment strategies. This method can efficiently converge in complex combinatorial problems and provide feasible solutions that meet enterprise operational requirements. By comparing and evaluating different scenarios, the practical effects of warehouse network adjustment and transportation mode optimization on cost control and green development can be clearly demonstrated. Based on real business practices, this study adopts quantitative analysis and optimization methods to provide K Company with practical improvement strategies. The findings indicate that distribution network optimization is not only a key approach for enterprises to reduce costs, but also an important means to achieve green development and strengthen market competitiveness, offering direct guidance for K Company’s future operations.
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