考虑减排强度的社区团购中心仓选址研究——以云南省为例
Research on the Site Selection of Community Group Buying Center Warehouses Considering Emission Reduction Intensity—A Case Study of Yunnan Province

随着环境保护意识的增强和绿色物流理念的推广，低碳发展逐渐成为各界关注的焦点。针对社区团购冷链产品的“网络中枢”中心仓选址优化问题，本文构建了以总成本最小化和碳排放强度最小化为双重目标的决策模型。在模型中引入碳排放强度等约束条件，通过加权处理兼顾成本与碳排放的优化需求，实现不同目标的单位和数量级差异消除，并提供动态调整的可能性。为求解该模型，本文采用遗传算法，最后结合实际数据对云南省某社区团购仓配网络体系进行优化分析。结果表明：(1) 在云南省设立昆明、曲靖、红河和大理四个中心仓库为最优方案；(2) 企业可依据低碳权重的不同设置，调整选址配置方案以更贴合社会发展的低碳导向。研究结论指出，该模型通过双目标优化兼顾碳排放和成本，能为社区团购网络体系的优化提供有效的借鉴。本文所建立的模型和设计的算法具有较好的实用性，可为不同区域的社区团购冷链产品提供低碳导向的选址优化决策支持。
With the growing awareness of environmental protection and the promotion of green logistics concepts, low-carbon development has gradually become a focal point of attention across various sectors. Focusing on the optimization of the “network hub” central warehouse location for community group buying of cold chain products, this paper constructs a decision-making model with dual objectives of minimizing total costs and minimizing carbon emission intensity. The model incorporates constraints such as carbon emission intensity, and through weighted processing, it balances the optimization needs of cost and carbon emissions, eliminating the differences in units and magnitudes of different objectives, and providing the possibility for dynamic adjustments. To solve this model, this paper employs a genetic algorithm, and finally, it optimizes and analyzes the warehouse distribution network system of a community group buying in Yunnan Province using actual data. The results indicate that: (1) Establishing four central warehouses in Kunming, Qujing, Honghe, and Dali in Yunnan Province is the optimal solution; (2) Enterprises can adjust the location configuration plan according to different low-carbon weights to better align with the low-carbon orientation of social development. The research conclusion points out that the model, through dual-objective optimization, considers both carbon emissions and costs, and can provide effective reference for the optimization of community group buying network systems. The model established in this paper and the designed algorithm have good practicality and can provide decision support for low-carbon-oriented location optimization of cold chain products for community group buying in different regions.